Data - AI / ML Engineer at FreeFlow Ventures · Kolkata · 4 - 7 years · ₹15L - ₹25L / yr · Posted 11 Apr 2026

Data - AI / ML Engineer
Full-Time | On-site, Kolkata | Immediate Joining | 4+ years experience
ABOUT US
Company Name: Freeflow ventures
We are a venture building and investment firm focused on emerging markets across India, the Middle East, and Africa. We work with early-stage startups -diagnosing gaps, structuring interventions, and preparing them for investor-readiness through a proprietary data and intelligence platform.
Our platform combines automated data verification, startup scoring, and structured workflow automation to bring consistency and credibility to early-stage investment decisions. We are at an active build and expansion phase, and this role sits at the core of that infrastructure.
ROLE OVERVIEW
We are looking for a Data - AI / ML Engineer who can own both the data pipelines that bring verified information into our platform and the intelligence models that turn that information into reliable startup scores.
This is a dual-responsibility role. You will be expected to build and maintain robust data infrastructure as well as develop, calibrate, and improve machine learning models. Both are equally important to the platform.
You will work closely with the Platform Owner and alongside a Backend Engineer who owns system integrations and workflow logic. Your work produces the scored intelligence output. The Backend Engineer's work connects that output to platform actions. The two roles are tightly interdependent and require close daily collaboration, especially in the first 30 days.
Note: You are the first technical hire on the platform team. The Backend Engineer joins the same week. Clear communication, well-defined handoff points, and shared documentation between the two of you are non-negotiable from Day 1.
WHAT YOU WILL DO
Data Pipeline
- Build and maintain pipelines that collect, clean, and normalize data from multiple external sources into a consistent, usable format
- Design connector architecture that allows individual data sources to be added, swapped, or removed without rebuilding the entire pipeline
- Implement automated data quality checks that catch bad data before it reaches the scoring layer -anomaly detection, constraint enforcement, and schema validation
- Build an automated eligibility screening system that verifies whether a startup has sufficient verified data before assessment begins
- Ensure the pipeline is resilient -critical data signals must have backup sources so a single vendor failure does not disrupt platform output
- Structure data storage to support different regulatory requirements across multiple countries -data from different regions must be handled according to the rules of that region
AI and Machine Learning
- Audit the existing scoring engine before making any changes -understand what it does, how it was built, and what would be lost if it were modified
- Calibrate scoring models against real portfolio data so that scores are meaningful, consistent, and comparable across different startup types and stages
- Build confidence scoring logic that determines when the system is certain enough to act autonomously and when it should route to human review
- Ensure every model output is explainable -investors must be able to see exactly which data points drove a score, not just the final number
- Build a feedback loop so that real-world outcomes feed back into the model over time, making it progressively more accurate
- Maintain a structured data store of assessment outputs and outcomes that the model uses to improve
Working With the Backend Engineer
- Define a clear data contract at the handoff point -what data you produce, in what format, and what the Backend Engineer can expect to receive
- Collaborate on trigger logic -what score thresholds or confidence drops should fire what system actions
- Align on data schema requirements so that the APIs the Backend Engineer builds conform to the structure your pipeline produces
- Communicate blockers early -the pipeline and backend system are built simultaneously, so delays on one side directly affect the other
- Document everything you build so the Backend Engineer and Platform Owner can understand, debug, and extend it without depending on you for every question
WHAT WE ARE LOOKING FOR
Skills are divided into two categories. Must Have means the role cannot function without it. Good to Have means it gives you an edge.
Skill
Priority
Data Engineering
Building and maintaining data pipelines from multiple sources
Must Have
Data normalization and schema design
Must Have
Automated data quality validation
Must Have
API integration across different source types
Must Have
Pipeline orchestration and scheduling
Must Have
Cloud infrastructure -storage, compute, and deployment
Must Have
Version control and code documentation
Must Have
AI and Machine Learning
Building and calibrating supervised machine learning models
Must Have
Model explainability -making model outputs traceable and interpretable
Must Have
Confidence scoring and threshold calibration
Must Have
Experiment tracking and model versioning
Must Have
Building feedback loops that improve models over time using real-world outcomes
Must Have
Natural language processing or document understanding
Good to Have
Vector databases and semantic search
Good to Have
Collaboration and Context
Ability to define clear data contracts and handoff points with backend engineers
Must Have
Clear written documentation of pipeline logic, model decisions, and failure modes
Must Have
Prior experience working in or with early-stage startups
Good to Have
Exposure to financial data, investment platforms, or data verification systems
Good to Have
WHAT WE OFFER
- Competitive compensation based on experience -discussed during the interview process
- Ownership of both the data and intelligence layers from Day 1 -this is not a support or maintenance role
- Direct access to the Platform Owner and Founder
- Close collaboration with a Backend Engineer from Day 1 -the two roles are designed to work as a unit
- Work on a genuinely novel problem in an emerging market context
- On-site Kolkata with a small, high-accountability team
- Opportunity to scale the platform across multiple international markets

About FreeFlow Ventures
About
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About NonStop io Technologies
NonStop io Technologies is a value-driven company with a strong focus on process-oriented software engineering. We specialize in Product Development and have a decade's worth of experience in building web and mobile applications across various domains. NonStop io Technologies follows core principles that guide its operations and believes in staying invested in a product's vision for the long term. We are a small but proud group of individuals who believe in the 'givers gain' philosophy and strive to provide value in order to seek value. We are committed to and specialize in building cutting-edge technology products and serving as trusted technology partners for startups and enterprises. We pride ourselves on fostering innovation, learning, and community engagement. Join us to work on impactful projects in a collaborative and vibrant environment.
Brief Description:
We're seeking an AI/ML Engineer to join our team. As AI/ML Engineer, you will be responsible for designing, developing, and implementing artificial intelligence (AI) and machine learning (ML) solutions to solve real-world business problems. You will work closely with engineering teams, including software engineers, domain experts, and product managers, to deploy and integrate Applied AI/ML solutions into the products that are being built at NonStop io. Your role will involve researching cutting-edge algorithms and data processing techniques, and implementing scalable solutions to drive innovation and improve the overall user experience.
Responsibilities
● Applied AI/ML engineering; Building engineering solutions on top of the AI/ML tooling available in the industry today. Eg: Engineering APIs around OpenAI
● AI/ML Model Development: Design, develop, and implement machine learning models and algorithms that address specific business challenges, such as natural language processing, computer vision, recommendation systems, anomaly detection, etc.
● Data Preprocessing and Feature Engineering: Cleanse, preprocess, and transform raw data into suitable formats for training and testing AI/ML models. Perform feature engineering to extract relevant features from the data
● Model Training and Evaluation: Train and validate AI/ML models using diverse datasets to achieve optimal performance. Employ appropriate evaluation metrics to assess model accuracy, precision, recall, and other relevant metrics
● Data Visualization: Create clear and insightful data visualizations to aid in understanding data patterns, model behaviour, and performance metrics
● Deployment and Integration: Collaborate with software engineers and DevOps teams to deploy AI/ML models into production environments and integrate them into various applications and systems
● Data Security and Privacy: Ensure compliance with data privacy regulations and implement security measures to protect sensitive information used in AI/ML processes
● Continuous Learning: Stay updated with the latest advancements in AI/ML research, tools, and technologies, and apply them to improve existing models and develop novel solutions
● Documentation: Maintain detailed documentation of the AI/ML development process, including code, models, algorithms, and methodologies for easy understanding and future reference.
Qualifications & Skills
● Bachelor's, Master's, or PhD in Computer Science, Data Science, Machine Learning, or a related field. Advanced degrees or certifications in AI/ML are a plus
● Proven experience as an AI/ML Engineer, Data Scientist, or related role, ideally with a strong portfolio of AI/ML projects
● Proficiency in programming languages commonly used for AI/ML. Preferably Python
● Familiarity with popular AI/ML libraries and frameworks, such as TensorFlow, PyTorch, scikit-learn, etc.
● Familiarity with popular AI/ML Models such as GPT3, GPT4, Llama2, BERT etc.
● Strong understanding of machine learning algorithms, statistics, and data structures
● Experience with data preprocessing, data wrangling, and feature engineering
● Knowledge of deep learning architectures, neural networks, and transfer learning
● Familiarity with cloud platforms and services (e.g., AWS, Azure, Google Cloud) for scalable AI/ML deployment
● Solid understanding of software engineering principles and best practices for writing maintainable and scalable code
● Excellent analytical and problem-solving skills, with the ability to think critically and propose innovative solutions
● Effective communication skills to collaborate with cross-functional teams and present complex technical concepts to non-technical stakeholders
Role Overview
We are looking for an AI/ML Engineer with 2 - 6 years of industry experience to develop and deploy machine learning solutions for industrial and smart manufacturing use cases. The role involves working with real-world industrial data, developing predictive and analytical models, and translating business and operational requirements into scalable AI/ML solutions.
The ideal candidate should have strong fundamentals in machine learning, Python, data processing, model development, and deployment, along with an interest in applying AI to manufacturing, industrial automation, and operational optimization.
Key Responsibilities
- Design, develop, train, and evaluate machine learning models for industrial and manufacturing use cases.
- Analyze large and complex datasets to identify patterns, trends, anomalies, and opportunities for optimization.
- Perform data preprocessing, feature engineering, model selection, and performance evaluation.
- Develop solutions for use cases such as predictive maintenance, anomaly detection, quality prediction, process optimization, forecasting, and equipment monitoring.
- Work with structured and time-series data generated from industrial equipment, machines, sensors, and operational systems.
- Develop and optimize ML pipelines for data preparation, model training, validation, and deployment.
- Collaborate with domain experts, data engineers, software engineers, and business stakeholders to understand requirements and translate them into technical solutions.
- Deploy machine learning models into production environments and monitor model performance.
- Troubleshoot model and data-related issues and continuously improve model accuracy, reliability, and scalability.
- Develop reusable code, APIs, and components to integrate ML models with enterprise and industrial applications.
- Document models, methodologies, experiments, results, and technical implementations.
- Stay updated with emerging AI/ML techniques, industrial AI trends, and smart manufacturing technologies.
Required Technical Skills
- Strong programming experience in Python.
- Good understanding of Machine Learning algorithms and concepts.
- Experience with libraries/frameworks such as Scikit-learn, Pandas, NumPy, and preferably TensorFlow or PyTorch.
- Strong understanding of data preprocessing, feature engineering, model training, validation, and evaluation.
- Experience working with time-series data is preferred.
- Good understanding of statistical concepts and data analysis.
- Experience with SQL and relational databases.
- Understanding of model deployment and productionization of ML solutions.
- Familiarity with Git and software development best practices.
- Good problem-solving and analytical skills.
Preferred Skills
- Experience in Industrial AI, Smart Manufacturing, Industry 4.0, or Industrial IoT (IIoT).
- Experience with predictive maintenance, anomaly detection, forecasting, or quality inspection.
- Exposure to sensor data, machine/equipment data, telemetry, or real-time industrial data.
- Knowledge of computer vision for manufacturing or quality inspection use cases.
- Exposure to cloud platforms such as AWS, Azure, or GCP.
- Familiarity with Docker, Kubernetes, or CI/CD for ML deployment.
- Knowledge of MLOps concepts and tools.
- Exposure to Generative AI/LLMs is an added advantage.
Hiring for AI Engineer
Exp: 5 - 8 yrs
Edu : BE/B.Tech/MCA
Work Location : Pune
Skill Set:
Total experience ranging from 5 - 8 years in software engineering/AI roles
Min 5 years strong programming experience in Python or Typescript is a MUST
Min 2.5 years hands-on experience in AI with LLMs, RAG pipelines, and AI frameworks
Experience with cloud platforms (AWS/Azure/GCP)
Job Overview
We are looking for an experienced AI/ML Engineer with strong full-stack development skills to design, develop, and deploy AI-powered applications. The ideal candidate should be proficient in Python backend development, frontend technologies, and LLM integration, with the ability to build end-to-end AI-native products, custom dashboards, and lightweight applications.
This role focuses on applying AI to real-world business problems through rapid prototyping, prompt engineering, Retrieval-Augmented Generation (RAG), and scalable application development.
Key Responsibilities
- Design, develop, and deploy end-to-end AI-powered applications.
- Build backend services and REST APIs using Python.
- Develop responsive frontends using React, Next.js, or similar frameworks.
- Integrate LLM APIs such as OpenAI, Claude, and Hugging Face into production applications.
- Build custom dashboards, internal tools, micro-apps, and AI-driven business solutions.
- Implement prompt engineering, embeddings, RAG pipelines, and context-aware AI systems.
- Rapidly prototype and validate ideas using modern AI-assisted development workflows.
- Optimize application performance, scalability, reliability, and AI usage costs.
- Work with data processing libraries such as Pandas and NumPy.
- Collaborate with product and business teams to translate requirements into functional AI solutions.
- Take ownership of features from ideation and development through testing, deployment, and production support.
Required Skills & Qualifications
- 2+ years of experience in software engineering, AI engineering, or application development.
- Strong proficiency in Python and backend development.
- Hands-on experience with React, Next.js, or similar frontend technologies.
- Practical experience integrating LLM APIs such as OpenAI, Claude, or Hugging Face.
- Understanding of REST APIs, microservices, and system design principles.
- Knowledge of prompt engineering, embeddings, and RAG architectures.
- Experience with data processing using Pandas and NumPy.
- Ability to independently build, test, and deploy full-stack applications.
- Strong problem-solving, debugging, and analytical skills.
- Ability to work in a fast-paced environment with a strong ownership mindset.
Good to Have
- Experience with LangChain, LlamaIndex, or similar AI frameworks.
- Familiarity with vector databases such as Pinecone, Weaviate, or Supabase.
- Experience building AI chat interfaces, copilots, assistants, and custom dashboards.
- Familiarity with cloud platforms, application deployment, and production monitoring.
- Experience with AI-assisted coding tools and rapid prototyping workflows.
What We Are Looking For
- A full-stack AI engineer who is comfortable working across both backend and frontend development.
- Someone focused on building practical AI-powered products rather than only training machine learning models.
- A developer who can prototype quickly, validate ideas, and iterate efficiently using a “vibe coding” approach.
- A self-driven professional who can take ownership of a feature from concept to production.
Please note that this job is only for Ahmedabad location.
Kody Technolab Limited is seeking an experienced AI/ML Engineer to design, develop, and deploy cutting-edge Artificial Intelligence and Machine Learning solutions. The ideal candidate will have
strong expertise in Machine Learning, Deep Learning, Generative AI, LLMs, MLOps, and cloud-based AI deployments.
Key Responsibilities
• Design, develop, and deploy Machine Learning and Deep Learning models for classification, regression, recommendation systems, NLP, Computer Vision, and Generative AI applications.
• Build and maintain end-to-end ML pipelines including data preprocessing, feature engineering, model training, validation, evaluation, and deployment.
• Develop AI solutions using PyTorch, TensorFlow, Scikit-learn, Hugging Face, and related frameworks.
• Work with Large Language Models (LLMs) and foundation models such as GPT, BERT, Llama, Claude, and Stable Diffusion.
• Collaborate with product, engineering, and business teams to translate requirements into scalable AI solutions.
• Optimize model performance, scalability, and reliability for production environments.
• Implement MLOps best practices using tools such as MLflow, Docker, Kubernetes, and Kubeflow.
• Stay updated with emerging trends and research in AI, ML, Deep Learning, and Generative AI.
Required Qualifications
• Bachelor’s or Master’s degree in Computer Science, Data Science, Artificial Intelligence, Mathematics, or a related field.
• 7+ years of hands-on experience in AI/ML product development.
• Strong proficiency in Python and ML frameworks including Scikit-learn, TensorFlow, PyTorch, and Hugging Face.
• Experience with Generative AI, LLMs, GANs, VAEs, diffusion models, and prompt engineering.
• Strong understanding of the ML lifecycle including model training, tuning, deployment, monitoring, and optimization.
• Experience with MLOps tools such as MLflow, Docker, Kubeflow, and CI/CD pipelines.
• Experience with AWS, Azure, or GCP cloud platforms.
• Strong problem-solving and analytical skills.
Preferred Skills
• Fine-tuning and deployment of Large Language Models.
• Experience with RAG (Retrieval Augmented Generation) architectures.
• Contributions to open-source AI projects or research publications.
• Knowledge of model interpretability, data annotation, and feature engineering.
• C++ experience for high-performance AI applications.
Why Join Kody Technolab Limited?
Opportunity to work on innovative AI products, Generative AI solutions, robotics integrations,
and enterprise-scale applications while collaborating with a highly skilled technology team.
Visit the Website to know more about us.
Company Website - Kody Technolab | Deep Tech Company in Robotics & AI Solution
Kody Robots | Robotics Company in India for Autonomous Robots
This is a remote position.
About Leegality:
Leegality works with large Indian businesses to digitally transform critical compliance processes in a fast, easy and secure way.
We have multiple products across 2 categories:
Document Infrastructure:
Products that help businesses build paperless processes at scale:
- Document Execution Workflow: A unified platform for businesses to digitally execute (eSign, eStamp, Template Pre-fill, Document Fraud Prevention etc.) agreements, forms and other documents in a compliant way. Currently in use by 2000+ Indian businesses from giants like HDFC and SBI Cards to high-growth disruptors like goDigit and Cars24.
- Contract Management: An AI-powered platform for businesses to quickly review, negotiate and take action on contract
- Signstation: A simple platform for businesses to digitally sign simple documents like invoices, policies and letters in a cost effective manner
Consent Infrastructure:
- Consentin: An end-to-end DPDP and Privacy compliance platform for Indian businesses
- Consentin Lens: A data discovery platform for businesses to identify the personal data they collect and store.
If you’re interested in building mission critical software that operates at population scale (75 million + Indians have signed at least one document through Leegality) then join Leegality.
Curious about our impact? Explore our customer success stories: leegality.com/case-studies
Our Culture
At Leegality, trust, ownership, transparency, and having fun while doing meaningful work are core to how we operate — not just values on paper. Our team rated us an incredible 97 eNPS for FY 2023–24 — the highest among 175+ startups surveyed.
We focus deeply on helping our people grow and stay motivated. Some of the perks you’ll enjoy:
- Flexible working hours
- Hybrid work setup
- Bi-annual performance appraisals
- A culture that rewards initiative, curiosity, and impact
If you're looking for a place where you can make a real difference while working with smart, driven, and genuinely nice people, welcome to Leegality.
Location: Hybrid
Job Brief:
- As a Machine Learning Engineer specializing in Computer Vision (CV) and Natural Language Processing (NLP), you will develop solutions to interesting technical problems, exploring exciting growth opportunities and having a real impact on our product, particularly focusing on document and content intelligence.
- To ensure success, you should demonstrate solid data science knowledge and experience in a related ML, CV, or NLP role. A first-class engineer will be someone whose expertise enhances our systems for document intelligence and content processing
Responsibilities:
- Designing machine learning systems, self-running artificial intelligence (AI) software, and specialized models for Computer Vision and Natural Language Processing applications.
- Transforming data science prototypes and applying appropriate deep learning algorithms and tools to text and image/document data.
- Solving complex CV and NLP problems with multi-layered data types, such as image/document classification, information extraction, semantic search, and object detection.
- Optimizing existing machine learning models, with a focus on high-performance model deployment for CV and NLP tasks.
- Developing ML algorithms (including large language models/LLMs and computer vision models) to analyze huge volumes of historical text, image, and document data to make predictions and automate workflows.
- Running tests, performing statistical analysis, and interpreting test results for CV/NLP model performance.
- Documenting machine learning processes, model architectures, and data pipelines.
- Keeping abreast of developments in machine learning, Computer Vision, and Natural Language Processing.
Requirements:
- 3+ years of relevant experience in Machine Learning Engineering, with a strong focus on Computer Vision and/or Natural Language Processing.
- Advanced proficiency with Python.
- Extensive knowledge of ML frameworks, libraries (e.g., PyTorch, Transformers), data structures, data modeling, and software architecture.
- Experience with building and maintaining scalable RESTful APIs (e.g., FastAPI).
- In-depth knowledge of mathematics, statistics, deep learning (CNNs, RNNs, Transformers), and algorithms.
- Superb analytical and problem-solving abilities, especially for unstructured data challenges.
- Great communication and collaboration skills.
- Excellent time management and organizational abilities.
- Experience with cloud platforms (e.g., AWS) for model deployment and MLOps.
Recruitment Process:
- Our hiring process combines AI-powered evaluations with structured interviews to ensure a fair and seamless experience.
- You will be contacted via email with the next steps upon being shortlisted.
- The process may include Assessments, AI-enabled interviews, and In-Person Interviews with our team.
- Final selection and CTC will be based on your overall performance and experience.
Apply directly through our career page: https://careers.leegality.com/jobs/Careers
For more information about us please visit our:
Our Company and Culture: https://bit.ly/3Iqm5SB
Our Website: www.leegality.com/
Our LinkedIn Page: www.linkedin.com/company/leegality/
Leegality's Privacy Notice: https://www.leegality.com/employee-privacy-notice
The recruiter has not been active on this job recently. You may apply but please expect a delayed response.
ML DEVELOPER
Hyperworks Imaging is a cutting-edge technology company based out of Bengaluru, India since 2016. Our team uses the latest advances in deep learning and multi-modal machine learning techniques to solve diverse real world problems. We are rapidly growing, working with multiple companies around the world.
JOB OVERVIEW
We are seeking a talented and results-oriented ML Developer to join our growing team in India. In this role, you will be responsible for developing and implementing new advanced ML algorithms and AI agents for creating AI assistants of the future.
The ideal candidate will work on a complete ML pipeline starting from extraction, transformation and analysis of data to developing novel ML algorithms. The candidate will implement latest research papers and closely work with various stakeholders to ensure data-driven decisions and integrate the solutions into a robust ML pipeline.
RESPONSIBILITIES:
- Create AI agents using Model Context Protocols (MCPs), Claude Code, DsPy etc.
- Develop custom evals for AI agents.
- Build and maintain ML pipelines
- Optimize and evaluate ML models to ensure accuracy and performance.
- Define system requirements and integrate ML algorithms into cloud based workflows.
- Write clean, well-documented, and maintainable code following best practices
REQUIREMENTS:
- 2-3+ years of experience in data science, machine learning, or a similar role.
- Demonstrated expertise with python, PyTorch, and TensorFlow.
- Graduated/Graduating with B.Tech/M.Tech/PhD degrees in Electrical Engg./Electronics Engg./Computer Science/Maths and Computing/Physics
- Has done coursework in Linear Algebra, Probability, Image Processing, Deep Learning and Machine Learning.
- Has demonstrated experience with Model Context Protocols (MCPs), DSPy, AI Agents, MLOps etc
WHO CAN APPLY:
Only those candidates will be considered who,
- have relevant skills and interests
- can commit full time
- Can show prior work and deployed projects
- can start immediately
Please note that we will reach out to ONLY those applicants who satisfy the criteria listed above.
SALARY DETAILS: Commensurate with experience.
JOINING DATE: Immediate
JOB TYPE: Full-time
ABOUT
The Persona Labs is building a new kind of social platform focused on something most social products do not explicitly optimize for: helping people become real friends.
We want to help people discover interesting people around them, find meaningful common ground, start low-pressure interactions, continue promising conversations, create shared experiences, and ultimately build real-life friendships.
DISCOVER → CURIOSITY → COMPATIBILITY → INTERACTION → UNDERSTAND → IRL EXPERIENCE → FRIENDSHIP
THE AI LAYER - COMPANION INTELLIGENCE
Alongside the platform, we are building a proactive personal AI companion that learns about the user and helps them navigate this journey through personalized recommendations, suggestions, reminders, conversations, and experiences.
THE OPPORTUNITY
We are looking for a Founding ML Engineer to build the intelligence layer of the platform from the ground up. This is a 0→1 Applied AI / ML role where you will work directly with the founder and Product Engineer to turn ambiguous problems around users, relationships, recommendations and personal intelligence into working systems.
You will be expected to:
Understand the problem → identify the signals → design the intelligence system → prototype → evaluate → deploy → learn → improve.
WHAT YOU WILL BUILD & OWN
USER INTELLIGENCE
User representations, behavioural models, interests, preferences, contextual signals, and evolving understanding of the user. MEMORY Short- and long-term memory, episodic/preference/relationship memory, retrieval, relevance and updating.
RECOMMENDATION & MATCHING
People discovery, compatibility, activity/experience recommendations, and personalized ranking.
INTENT & INTEREST
Infer what the user is trying to do and learn what they care about from behaviour, not only declared interests.
RANKING
Decide what should appear first across potentially thousands of relevant people, activities or experiences.
CONTENT INTELLIGENCE
Classification, toxicity, spam, policy signals, quality, relevance, and semantic understanding.
RELATIONSHIP INTELLIGENCE
Reciprocity, interaction health, shared interests, progression, declining engagement and shared activity.
NEXT-BEST-ACTION
Determine the most useful action now: show a person, suggest a question, recommend an activity, reconnect, or do nothing.
TRUST / SAFETY INTELLIGENCE
Fake-account signals, spam, abuse, behavioural anomalies, risky interactions and moderation assistance.
COMPANION INTELLIGENCE
Use signals and outputs to help the companion decide what to say, suggest, recommend or not do.
WHAT YOUR DAY-TO-DAY LOOKS LIKE
• Translate ambiguous product problems into ML/AI system designs.
• Build models and intelligence pipelines using behavioural, relational and contextual signals.
• Develop recommendation, matching and personalization systems.
• Design memory and retrieval systems that help the companion understand the user over time.
• Build and evaluate LLM-powered and agentic workflows.
• Decide when to use traditional ML, rules, retrieval, ranking or LLMs.
• Prototype quickly, test assumptions and iterate based on real user behaviour.
• Work closely with the founder and Product Engineer to turn intelligence into product experiences.
• Design APIs and production systems that bring ML/AI capabilities into the application.
• Build evaluation, monitoring and feedback loops so the intelligence improves over time.
WHO SHOULD APPLY
• Experience: 0–4 years’ experience, including exceptional fresh graduates. Strong 1–3 year engineers and experienced 3–4 year product builders are welcome.
• Strong foundations in ML, Python, statistics and software engineering.
• Evidence of Building: Experience with AI/ML projects, recommendation systems, LLM applications or personalization is highly valued.
• Strong evidence of building: Shipped projects, research, hackathons, internships, open source or startup work.
WHAT WE LOOK FOR
MACHINE LEARNING DEPTH
Can you understand the modelling problem underneath the application?
RECOMMENDATION & PERSONALIZATION
Can you reason about relevance, ranking, cold start and behavioural signals?
AI ENGINEERING
Can you turn LLMs and agents into reliable product capabilities rather than simple API wrappers?
USER INTELLIGENCE
Can you design systems that gradually understand a person from sparse and changing signals?
SYSTEMS THINKING
Can you move from a model to a production system with APIs, data, latency, cost and monitoring?
EVALUATION MINDSET
Can you determine whether the intelligence actually helped the user?
PRODUCT JUDGMENT
Can you decide what the system should do when there is no predefined answer?
SPEED OF EXECUTION
Can you move from idea → prototype → evaluation → production quickly and responsibly?
BUILD WITH US
You will join at a stage where many of the answers do not exist yet. You will not simply implement a model someone else selected; you will help decide how the product learns to understand people.
CAREERS:
Apply with your resume, GitHub, portfolio or shipped work.
https://forms.gle/12YpUSBY2Sqs5xjp8
www.thepersonalabs.com
GEMBA CONCEPTS
Experience: ~3–5 years Type: Full-time
AI/ML Engineer
Location: Bengaluru, India (Hybrid)
About Gemba Concepts
Gemba Concepts is a lean manufacturing and technology consulting firm helping clients across pharma, manufacturing, and logistics
modernize how they operate. We build production systems that sit close to the shop floor — warehouse management, manufacturing
traceability, and an applied AI/ML platform whose flagship use cases are visual quality inspection and predictive maintenance. We’re a
tight engineering team that ships real systems for demanding, often regulated, environments.
The Role
We’re looking for an AI/ML Engineer to take ML capabilities from prototype to production. You’ll own models end-to-end — framing the
problem with stakeholders, building and validating the model, and deploying it as a reliable service that holds up against real-world, messy
industrial data. This is a hands-on building role, not a pure research seat: your work goes into client-facing systems.
What You’ll Do
Build and ship computer vision models for visual quality inspection (defect detection, classification, segmentation) that perform under
real factory lighting, throughput, and edge-case conditions.
Develop predictive maintenance models using sensor/time-series data — anomaly detection, remaining-useful-life estimation, failure
prediction.
Own the full ML lifecycle: data pipelines, feature engineering, training, evaluation, and deployment, with proper versioning and monitoring.
Deploy and serve models in production on Azure (AKS), and keep them healthy — track drift, retraining triggers, and latency.
Integrate LLM-based capabilities (we use the Claude API and self-hosted open models) into delivery and product workflows where they
add leverage.
Collaborate with product, engineering, and domain experts to translate fuzzy operational problems into well-scoped ML solutions — and to
know when ML is not the right answer.
Communicate results and limitations clearly to non-ML stakeholders, including clients.
What We’re Looking For
3–5 years of hands-on experience building and deploying ML models in production (not just notebooks or coursework).
Strong Python and the modern ML stack — PyTorch or TensorFlow, scikit-learn, NumPy/Pandas.
Solid grounding in at least one of: computer vision (CNNs, object detection/segmentation, image preprocessing) or time-series /
anomaly detection.
Practical MLOps experience: containerization (Docker), model serving, experiment tracking, and deploying on a cloud platform — Azure /
Kubernetes (AKS) is a strong plus.
Comfort working with imperfect, real-world data — labeling strategy, class imbalance, data drift, and validation that reflects production
reality.
Good engineering hygiene (Git, testing, code review) and the ability to write code others can build on.
Nice to Have
Experience with industrial / manufacturing data or regulated environments (pharma, 21 CFR Part 11 awareness).
Hands-on LLM integration experience — RAG, prompt engineering, working with APIs or self-hosted models (vLLM, Qwen, etc.).
Edge deployment experience (running CV models on-device / near the line).
Exposure to data pipeline tooling and orchestration.
What You’ll Get
Real ownership of ML systems that go into production for serious clients.
A lean, senior-heavy team where you ship fast and learn across the stack.
Direct exposure to applied AI in manufacturing — a domain where the work has tangible, physical impact

Job Summary
We are looking for an experienced AI/ML Engineer to design, develop, deploy, and maintain machine learning and AI solutions that address complex business problems. The ideal candidate should have strong hands-on experience in Python, Machine Learning, Generative AI, LLMs, and AI/ML deployment, with the ability to work across the complete AI/ML lifecycle.
Key Responsibilities
- Design, develop, and deploy scalable Machine Learning and AI models for real-world business use cases.
- Build and optimize ML pipelines covering data preparation, feature engineering, model development, evaluation, and deployment.
- Develop solutions using Generative AI, Large Language Models (LLMs), NLP, and deep learning.
- Work with LLMs, prompt engineering, embeddings, vector databases, and Retrieval-Augmented Generation (RAG) architectures.
- Integrate AI/ML models with enterprise applications and APIs.
- Fine-tune and evaluate ML/LLM models based on business requirements.
- Implement MLOps practices for model versioning, deployment, monitoring, and continuous improvement.
- Collaborate with Data Scientists, Software Engineers, Architects, Product Managers, and business stakeholders.
- Conduct model performance evaluation, optimization, and troubleshooting.
- Ensure AI solutions meet requirements around security, scalability, reliability, responsible AI, and data privacy.
- Stay current with emerging AI/ML technologies, frameworks, and industry best practices.
Required Skills
- Strong programming experience in Python.
- Strong understanding of Machine Learning algorithms, statistics, and data structures.
- Hands-on experience with ML frameworks such as TensorFlow, PyTorch, Scikit-learn, or equivalent.
- Experience with Generative AI and LLMs such as OpenAI, Azure OpenAI, Claude, Gemini, or open-source models.
- Strong knowledge of Prompt Engineering, RAG, embeddings, vector databases, and AI agents.
- Experience with NLP, deep learning, or computer vision is an advantage.
- Experience developing and consuming REST APIs and microservices.
- Working knowledge of SQL and NoSQL databases.
- Experience with cloud platforms such as Azure, AWS, or GCP.
- Understanding of Docker, Kubernetes, CI/CD, and MLOps.
- Familiarity with Git and modern software development practices.
Preferred Qualifications
- Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or a related field.
- 4 years of relevant experience in AI/ML engineering or a related field.
- Experience building and deploying production-grade AI/ML solutions.
- Enterprise application development experience.
- Experience with Azure OpenAI, AWS Bedrock, Vertex AI, or similar managed AI platforms.
- Experience with LangChain, LlamaIndex, Semantic Kernel, or comparable AI frameworks is a plus.
- Experience with AI/ML model monitoring, evaluation, and optimization.
What You Bring
- Strong problem-solving and analytical skills.
- Ability to translate business requirements into practical AI/ML solutions.
- Strong software engineering and debugging capabilities.
- Ability to work independently as well as collaboratively in a cross-functional environment.
- Good communication skills with the ability to explain complex AI concepts to technical and non-technical stakeholders.
Keywords
AI Engineer | ML Engineer | Machine Learning | Generative AI | LLM | Python | NLP | Deep Learning | RAG | Prompt Engineering | AI Agents | Azure OpenAI | AWS Bedrock | MLOps | TensorFlow | PyTorch | Scikit-learn | Vector Database | Cloud AI
Location: Gurugram
Work mode: Hybrid













