Software Engineer (Machine learning & Recommendation) at Mercari, Inc · Bengaluru (Bangalore) · 6 - 9 years · Profitable · Posted 14 Apr 2026

Introduction
About Us:
Mercari is a Japan-based C2C marketplace company founded in 2013 with the mission to “Create value in a global marketplace where anyone can buy & sell.” From being the first tech unicorn from Japan before its IPO in 2018 we have come a long way towards becoming a global player and continuously and diligently work towards our transformation journey with a strong focus on our mission.
Since its inception, Mercari Group has worked to grow its services, investing in both our people and technology. Over time Mercari has expanded from being the top player in the C2C marketplace in Japan to new geographies like the U.S. We have also successfully launched new businesses such as Merpay, which is a mobile payment service platform with a vision to create a society where anyone can realize their dreams through a new ecosystem centered not only on payment service but also on credit. Today, Mercari Group is made up of multiple subsidiary businesses including logistics, B2C platform, blockchain, and sports team management.
For our services to be utilized by people worldwide; however, there is still a mountain of work ahead of us. This endeavor naturally requires the capability of the best talent and minds, and that is exactly the reason for us to launch the India Center of Excellence. With your help, we will continue to take on the world stage and strive to grow into a successful global tech company.
Our Culture:
To achieve our mission at Mercari, our organization and each of our employees share the same values and perspectives. Our individual guidelines for action are defined by our four values: Go Bold, All for One, Be a Pro and Move Fast. Our organization is also shaped by our four foundations: Sustainability, Diversity & Inclusion, Trust & Openness, and Well-being for Performance. Regardless of how big Mercari gets, the culture will remain essential to achieving our mission and something we want to preserve throughout our organization. We invite you to read the Mercari Culture Doc which summarizes the behaviors and mindset shared by Mercari and its employees. We continue to build an environment where all of our members of diverse backgrounds are accepted and recognized, and where they can thrive while holding dear to Mercari’s culture.
Work Responsibilities
- Machine learning engineers working in the Recommendation domain develop the functions and services of the marketplace app Mercari through the development and maintenance of machine learning systems like Recommender systems while leveraging necessary infrastructure and companywide platform tools.
- Mercari is actively applying advanced machine learning technology to provide a more convenient, safer, and more enjoyable marketplace. Machine learning engineers use the cloud and Kubernetes to operate and improve machine learning systems.
Bold Challenges
- We are looking for people who are interested in our services, mission, and values, and want to work where engineers can go bold, use the latest technology, make autonomous decisions, and take on challenges at a rapid pace.
- Develop and optimize machine learning algorithms and models to enhance recommendation system to improve discovery experience of users
- Collaborate with cross-functional teams and product stakeholders to gather requirements, design solutions, and implement features that improve user engagement
- Conduct data analysis and experimentation with large-scale data sets to identify patterns, trends, and insights that drive the refinement of recommendation algorithms
- Utilize machine learning frameworks and libraries to deploy scalable and efficient recommendation solutions.
- Monitor system performance and conduct A/B testing to evaluate the effectiveness of features.
- Continuously research and stay updated on advancements in AI/machine learning techniques and recommend innovative approaches to enhance recommendation capabilities.
Minimum Requirements:
- Over 5-9 years of professional experience in end-to-end development of large-scale ML systems in production
- Strong experience demonstrating development and delivery of end-to-end machine learning solutions starting from experimentation to deploying models, including backend engineering and MLOps, in large scale production systems.
- Experience using common machine learning frameworks (e.g., TensorFlow, PyTorch) and libraries (e.g., scikit-learn, NumPy, pandas)
- Deep understanding of machine learning and software engineering fundamentals
- Basic knowledge and skills related to monitoring system, logging, and common operations in production environment
- Communication skills to carry out projects in collaboration with multiple teams and stakeholders
Preferred skills:
- Experience developing Recommender systems utilizing large-scale data sets
- Basic knowledge of enterprise search systems and related stacks (e.g. ELK)
- Functional development and bug fixing skills necessary to improve system performance and reliability
- Experience with technology such as Docker and Kubernetes
- Experience with cloud platforms (AWS, GCP, Microsoft Azure, etc.)
- Microservice development and operation experience with Docker and Kubernetes
- Utilizing deep learning models/LLMs in production
- Experience in publications at top-tier peer-reviewed conferences or journals
Employment Status
Full-time
Office
Bangalore
Hybrid workstyle
- We believe in high performance and professionalism. We work from office for 2 days/week and work from home 3 days/week
- To build a strong & highly-engaged organization in India, we highly encourage everyone to work from our Bangalore office, especially during the initial office setup phase
- We will continue to review and update the policy to address future organizational needs
Work Hours
- Full flextime (no core time)
*Flexible to choose working hours other than team common meetings
Media
Owned Media
- Mercari Engineering Portal
- AI at Mercari portal
- Mercan - Introduces the people that make Mercari
- Mercari US Blog
Related Articles
- Development Platforms and Platformers: On Rising to the Global Standard Ken Wakasa, Mercari CTO | mercan
- “I'm Not a Talented Engineer” Insists the Member-Turned-Manager Revamping Our Internal CS Tool | mercan
- Personalize to globalize:How Mercari is reshaping their app, their company, and the world | mercan
- The Providers of the Safe and Secure Mercari Experience: The TnS Team, Introduced by Its Members! | mercan

About Mercari, Inc
About
Launched in 2013 and becoming the first Unicorn company in Japan, Mercari Group is a Japan-based corporate group operating in both Japan and the US. Our mission is to create value in a global marketplace where everyone can buy and sell.
Mercari is the largest marketplace platform with over 20 million monthly users in Japan. Through the Mercari app, users can sell their used or unwanted items to those who need them just by taking a photo and entering in some basic information. We are constantly developing our app to provide an environment where anyone can conduct transactions easily, safely, and securely. As part of these efforts, we have invested in the latest technologies such as AI and machine learning, and have released various functions such as escrow payment, AI listing, and barcode listing.
The app currently operates in Japan and the US, with 5.6 million monthly users in the US (as of 2022.3).
We have also successfully launched new businesses such as our mobile payment service Merpay. Today, Mercari Group is made up of multiple subsidiary businesses, including those involved in logistics, B2C e-commerce, blockchain, and sports team management.
Mercari India located in Bengaluru will harness the infinite power of technology to create high-quality service where our people come together to build products that will further strengthen our leadership position in a global product market.
Website
Industry
Technology, Information and Internet
Company video
Candid answers by the company
Similar jobs (10)
Key Responsibilities:
- Develop and deploy machine learning, deep learning, and NLP models for various business use cases.
- Build end-to-end ML pipelines including data preprocessing, feature engineering, training, evaluation, and production deployment.
- Optimize model performance and ensure scalability in production environments.
- Work closely with data scientists, product teams, and engineers to translate business requirements into AI solutions.
- Conduct data analysis to identify trends and insights.
- Implement MLOps practices for versioning, monitoring, and automating ML workflows.
- Research and evaluate new AI/ML techniques, tools, and frameworks.
- Document system architecture, model design, and development processes.
Required Skills:
- Strong programming skills in Python (NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch, Keras).
- Hands-on experience in building and deploying, finetuning ML/DL models in production.
- Good understanding of machine learning algorithms, neural networks, NLP, and computer vision.
- Experience with REST APIs, Docker, Kubernetes, and cloud platforms (AWS/GCP/Azure).
- Working knowledge of MLOps tools such as MLflow, Airflow, DVC, or Kubeflow.
- Familiarity with data pipelines and big data technologies (Spark, Hadoop) is a plus.
- Strong analytical skills and ability to work with large datasets.
- Excellent communication and problem-solving abilities.
- Experience in deploying models using cloud services (AWS Sagemaker, GCP Vertex AI, etc.).
- Experience in LLM fine-tuning or Generative AI, Voice AI, is an added advantage.
Educational Qualification:
- Bachelor’s or Master’s degree in Computer Science, Data Science, AI, Machine Learning, IT, from IIT/NIT colleges strongly preferred
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
Strong AI Engineer / Machine Learning Engineer profiles.
2
Mandatory (Experience 1) – Must have minimum 3+ years of hands-on experience in Data Science, Machine Learning, Applied AI, NLP, Deep Learning, or Generative AI solutions.
3
Mandatory (Experience 2) – Must have strong hands-on experience in Python programming, SQL, data analysis, feature engineering, model development, and production-grade ML applications.
4
Mandatory (Experience 3) – Must have experience working with Machine Learning and Deep Learning frameworks such as PyTorch, TensorFlow, Keras, Scikit-learn, or equivalent.
5
Mandatory (Experience 4) – Must have hands-on experience working on NLP, embeddings, semantic search, text classification, document understanding, recommendation systems, or similar AI/ML use cases.
6
Mandatory (Experience 5) – Must have experience working with Large Language Models (LLMs) such as GPT, Llama, Mistral, Claude, Gemini, Phi, or similar foundation models.
7
Mandatory (Experience 6) – Must have hands-on experience building or implementing RAG (Retrieval Augmented Generation) systems, vector search, knowledge retrieval, embeddings, chunking, indexing, or semantic retrieval solutions.
8
Mandatory (Experience 7) – Must have experience working with Git, CI/CD practices, production environments, and scalable AI/ML systems.
9
Mandatory (CTC) – The CTC breakup offered will be 75% fixed + 25% variable, as per company policy.
10
Mandatory (Age) - Candidate's Age should be below 28 Years
We are looking for a Data Science & Machine Learning Senior Associate with 3–5 years of relevant experience in data science, machine learning, and analytics. The candidate will be responsible for developing predictive models, analyzing complex datasets, building scalable ML solutions, and supporting production-grade data science applications on cloud platforms.
Key Responsibilities
- Develop and implement machine learning and predictive analytics models.
- Perform data analysis, statistical modeling, and optimization to solve business problems.
- Build demand forecasting and predictive models using time-series and other advanced techniques.
- Work with large datasets using Python, SQL, PySpark, and cloud-based data platforms.
- Develop and maintain scalable data pipelines for ML model development and deployment.
- Implement MLOps practices including model deployment, monitoring, retraining, and data-drift detection.
- Collaborate with software engineers, product teams, and business stakeholders to convert business requirements into analytical solutions.
- Validate models for accuracy, robustness, bias, and production readiness.
- Create meaningful visualizations and communicate analytical insights to technical and non-technical stakeholders.
Required Skills
- Python
- SQL
- Data Science & Machine Learning
- Predictive Modeling
- Statistical Analysis
- Machine Learning Algorithms
- Optimization Techniques
- Google Cloud Platform (GCP)
- BigQuery
- Dataflow
- Dataproc
- Data Fusion
- Cloud SQL
- Airflow
- PySpark
- PostgreSQL
- Terraform
- Tekton
- APIs
- MLOps
Preferred Skill
- Java
Good to Have
- Demand Forecasting
- Time-Series Analysis
- Neural Networks
- Ensemble Methods
- Support Vector Machines (SVM)
- Regression and Cluster Analysis
- ML Model Testing
- Bias Detection and Data Drift Monitoring
- Production ML Deployment
- QlikSense
- Automotive or Supply Chain Analytics
Education
Bachelor's degree in Computer Science, Data Science, Engineering, Statistics, Mathematics, or a related technical field.Master's degree in a relevant quantitative or technical field is preferred.

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
Must of Skills/Experience
• System Design
• Python
• TensorFlow
• Google ADK or Lang Graph
• Lang Chain , Lang Graph
• Spark
• Agentic AI Design
• ML Ops
• MCP (client and server)
• FastAPI
• Doc Factory
• RAG
• Golang
• LLMs – Gemini, Open AI
• NLP
• Dev Assistant - AI based code - generation
(Qwen or Claude or Copilot)
• CI/CD
• Good in oral and written communication,
collaboration and be a team player
Good to have skills
• DevOps with K8
• Scripting
• Java
• REST API
• UV
• ReACT
• DocFactory
• Unix
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
Strong Data Scientist / AI Engineer / Generative AI Engineer profile.
2
Mandatory (Experience 1) - Must have 3+ years of hands-on experience in Data Science, Artificial Intelligence, Machine Learning, Deep Learning, NLP, or Generative AI application development.
3
Mandatory (Experience 2) - Must have strong hands-on experience in Python programming, backend development, API development, and production-grade application support.
4
Mandatory (Experience 3) - Must have experience working with Machine Learning and Deep Learning frameworks such as PyTorch, TensorFlow, Keras, or Scikit-learn.
5
Mandatory (Experience 4) - Must have hands-on experience in NLP use cases such as text classification, sentiment analysis, entity recognition (NER), semantic search, embeddings, or document understanding.
6
Mandatory (Experience 5) - Must have experience working with Large Language Models (LLMs) such as GPT, LLaMA, Mistral, Phi, Claude, Gemini, or similar models.
7
Mandatory (Experience 6) - Must have hands-on experience building or implementing Retrieval Augmented Generation (RAG) solutions, vector search, semantic search, or knowledge-based AI applications.
8
Mandatory (Experience 7) - Must have experience with Prompt Engineering and Generative AI frameworks such as LangChain, LangGraph, AI Agents, Azure OpenAI, or similar technologies.
9
Mandatory (Experience 8) - Must have experience developing, consuming, or integrating APIs using Python frameworks such as FastAPI, Flask, or similar technologies.
10
Mandatory (CTC) - The CTC breakup offered will be 75% fixed + 25% variable, as per company policy.
11
Preferred (Experience 1) - Experience with LLMOps/MLOps tools for monitoring, evaluation, experimentation, and versioning of AI models.
12
Preferred (Experience 2) - Exposure to Azure OpenAI, Azure Kubernetes Service (AKS), Kubernetes, cloud-native AI deployments, or distributed systems.
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












