Data Scientist at Top startup of India - News App · Noida · 6 - 10 years · ₹35L - ₹65L / yr (ESOP available) · Posted 26 Mar 2022

Requirements-
● B.Tech/Masters in Mathematics, Statistics, Computer Science or another quantitative field
● 2-3+ years of work experience in ML domain ( 2-5 years experience )
● Hands-on coding experience in Python
● Experience in machine learning techniques such as Regression, Classification,Predictive modeling, Clustering, Deep Learning stack, NLP.
● Working knowledge of Tensorflow/PyTorch
Optional Add-ons-
● Experience with distributed computing frameworks: Map/Reduce, Hadoop, Spark etc.
● Experience with databases: MongoDB

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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 Nexora Group
Nexora Group is a technology and innovation-driven organization dedicated to building intelligent solutions that leverage Artificial Intelligence, Machine Learning, Data Analytics, and emerging technologies. We are committed to fostering talent by providing aspiring professionals with practical exposure, mentorship, and opportunities to work on real-world projects.
Internship Overview
Nexora Group is looking for enthusiastic and driven AI/ML Interns to join our team. This internship is ideal for students and recent graduates who are passionate about Artificial Intelligence, Machine Learning, Deep Learning, and Generative AI. Interns will gain hands-on experience working on real-world AI projects, developing intelligent models, and solving complex business challenges using data-driven approaches.
Key Responsibilities
- Assist in developing, training, and evaluating Machine Learning models.
- Collect, clean, and preprocess datasets for AI/ML applications.
- Conduct exploratory data analysis and feature engineering.
- Work on Deep Learning, Natural Language Processing (NLP), and Computer Vision projects.
- Research and implement AI algorithms and emerging technologies.
- Support the development of Generative AI and Large Language Model (LLM)-based solutions.
- Optimize model performance and evaluate results using industry-standard metrics.
- Document project workflows, findings, and technical reports.
- Collaborate with cross-functional teams to develop innovative AI solutions.
Required Skills
- Basic understanding of Machine Learning and Artificial Intelligence concepts.
- Knowledge of Python programming.
- Familiarity with libraries such as NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch, or Keras.
- Understanding of data structures, algorithms, and statistics.
- Basic knowledge of Deep Learning, NLP, or Computer Vision concepts.
- Strong analytical and problem-solving skills.
- Good communication and teamwork abilities.
- Willingness to learn and adapt to new technologies.
Preferred Qualifications
- Experience with AI/ML projects, hackathons, or research work.
- Knowledge of Generative AI, Prompt Engineering, and LLMs.
- Familiarity with cloud platforms and AI deployment tools.
- Certifications in AI, Machine Learning, or Data Science are a plus.
- GitHub projects or portfolio showcasing AI/ML work.
Eligibility
- Undergraduate or postgraduate students pursuing Computer Science, Artificial Intelligence, Machine Learning, Data Science, Information Technology, or related fields.
- Recent graduates seeking practical industry experience.
- Candidates with a strong interest in AI innovation and research.
What You'll Gain
- Hands-on experience with real-world AI and Machine Learning projects.
- Mentorship from experienced AI professionals.
- Exposure to cutting-edge AI tools, frameworks, and technologies.
- Internship Completion Certificate.
- Letter of Recommendation based on performance.
- Opportunity for a Pre-Placement Offer (PPO) for outstanding performers.
- Professional networking and career development opportunities.
The recruiter has not been active on this job recently. You may apply but please expect a delayed response.
About the Internship
Nexora Group is looking for passionate and innovative students interested in Artificial Intelligence (AI) and Machine Learning (ML). This internship offers an opportunity to work on real-world AI projects, explore machine learning techniques, and gain hands-on experience with emerging technologies that are transforming industries worldwide.
Interns will collaborate with mentors, work on practical assignments, and develop industry-relevant skills in AI, ML, data-driven decision-making, and intelligent systems.
Key Responsibilities
- Assist in developing and testing Machine Learning models.
- Work on AI-based applications and automation projects.
- Analyze datasets and prepare data for model training.
- Research emerging AI and Machine Learning technologies.
- Evaluate model performance and improve accuracy.
- Create reports and documentation for assigned projects.
- Participate in project discussions, training sessions, and team meetings.
- Support the development of innovative AI-driven solutions.
Required Skills
- Basic knowledge of Python programming.
- Understanding of Artificial Intelligence and Machine Learning concepts.
- Familiarity with data analysis and statistics.
- Knowledge of Machine Learning libraries such as Scikit-learn, TensorFlow, or PyTorch is a plus.
- Strong analytical and problem-solving skills.
- Ability to learn new technologies quickly.
- Good communication and teamwork skills.
Eligibility
- B.Tech, M.Tech, BCA, MCA, B.Sc., M.Sc., or related disciplines.
- Students pursuing Computer Science, Artificial Intelligence, Data Science, Information Technology, Mathematics, or related fields.
- Freshers and recent graduates are encouraged to apply.
What You Will Learn
✅ Artificial Intelligence Fundamentals
✅ Machine Learning Algorithms
✅ Data Preprocessing & Model Training
✅ Generative AI Concepts
✅ Predictive Analytics
✅ AI Project Development
✅ Industry-Oriented Problem Solving
Benefits
✅ Internship Completion Certificate
✅ Letter of Recommendation (Performance-Based)
✅ Hands-on AI & ML Project Experience
✅ Professional Mentorship & Guidance
✅ Resume & LinkedIn Profile Enhancement
✅ Portfolio Development Support
✅ Exposure to Real-World AI Applications
The recruiter has not been active on this job recently. You may apply but please expect a delayed response.
AI/ML Engineer AI Operating System for Capital Markets Location Bangalore/Chennai Experience 5+ years Function Artificial Intelligence / Machine Learning Employment Type About Transient.AI Full-time Transient.AI is building a next-generation AI Operating System for capital markets — a unified intelligence layer that connects research, trading, compliance, and sales functions at banks and hedge funds. Today, these teams largely operate on disconnected legacy systems, forcing manual, expensive workarounds. Transient.AI replaces that fragmentation with a single AI-native layer built for institutional-grade compliance, security, and auditability. The company already has live products in market, including Caddie.AI (a research automation tool that cuts hedge fund research time significantly), ClarityRIA (helping sales teams identify the right investors in seconds), and CapFlo.AI (automated parsing of complex derivatives contracts). Founded by former traders and technologists from Goldman Sachs, Credit Suisse, UBS, and McKinsey, Transient.AI is headquartered in New York, with teams in Miami, Singapore, and India. The company has raised Series A funding and is scaling its engineering and product organization globally. Role Overview Transient.AI is hiring an experienced AI/ML Engineer to join its India engineering team in Bangalore/Chennai. This is a hands-on, build-from-scratch role — you'll be designing and shipping the core machine learning systems that power the company's flagship products, working closely with founders and senior engineers rather than inheriting existing infrastructure. Key Responsibilities • Design, build, and deploy machine learning and AI models that power Transient.AI's core products (research automation, document intelligence, investor matching, and workflow orchestration). • Workonapplied NLP/LLMsystems, including retrieval-augmented generation, structured extraction from unstructured financial documents, and model evaluation pipelines. • Partner closely with product and founding engineers to translate capital markets workflows into scalable AI systems. • Ownmodelperformance, reliability, and cost — from experimentation through production deployment. • Build and maintain data pipelines, feature stores, and evaluation frameworks to support rapid iteration. • Ensuresystems meet the compliance, auditability, and security standards required in regulated financial environments. What We're Looking For • 5+years ofexperience building and deploying machine learning or AI systems in production.• Strong hands-on experience with Python and modern ML/AI frameworks (PyTorch, TensorFlow, Hugging Face, LangChain, or equivalent). • Experience with LLMs — fine-tuning, prompt engineering, RAG architectures, or agentic systems — is highly valued. • Solid grounding in data structures, distributed systems, and MLOps practices (model serving, monitoring, versioning). • Prior experience at a strong product company, high-growth startup, or a top-tier engineering background • Comfort operating in an early-stage, high-ownership environment with limited process and high ambiguity. • Exposure to fintech, capital markets, or other regulated industries is a plus, though not mandatory. WhyJoin Transient.AI • Build core AI systems from the ground up — not maintain legacy code. • Workdirectly with founders who have deep, first-hand Wall Street experience (Goldman Sachs, Credit Suisse, UBS, McKinsey). • JoinaSeries A-funded company solving a real, expensive problem for institutional finance. • Bepart ofasmall, global team with outsized ownership and impact. .
We are seeking a Senior Data Science & ML Associate with 4+ years of applied ML experience to build and ship models end-to-end from data prep and feature engineering to training, evaluation, and deployment driving measurable business impact.
Key Responsibilities
• Build, train, and evaluate ML and deep-learning models
• Engineer features and prepare data at scale
• Deploy models and monitor production performance
• Partner with stakeholders to frame problems and metrics
• Communicate results and drive decisions
• Iterate on models from business feedback
Mandatory Skills
• 4+ years applied machine learning
• Strong Python (Pandas, NumPy, scikit-learn)
• Classical ML and deep learning (TensorFlow/PyTorch)
• Solid statistics and experiment design
• SQL and data wrangling at scale
• Model deployment / MLOps exposure
Nice to Have: NLP or computer vision; cloud ML (SageMaker, Azure ML)
We are hiring a Machine Learning Engineer to build and ship ML models into production.
Responsibilities
- Build, train and evaluate ML models
- Prepare features and training datasets
- Deploy models as APIs and monitor them
- Work with data and product teams on use cases
Requirements
- 1+ years of hands-on machine learning work
- Strong Python with scikit-learn, TensorFlow or PyTorch
- Experience deploying models is a plus
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
About the Role
We are looking for a highly skilled Data Scientist with strong expertise in Machine Learning, MLOps, and Generative AI. The ideal candidate will have hands-on experience in building scalable ML models, deploying them in production, and working with modern AI frameworks, including GenAI technologies.
Key Responsibilities
· Design, develop, and deploy machine learning models for real-world business problems
· Work on end-to-end ML lifecycle: data preprocessing, model building, evaluation, deployment, and monitoring
· Implement and manage MLOps pipelines for scalable and reproducible workflows
· Utilize tools like MLflow for experiment tracking, model versioning, and lifecycle management
· Develop and integrate Generative AI (GenAI) solutions such as LLM-based applications
· Collaborate with cross-functional teams (engineering, product, business) to translate requirements into AI solutions
· Optimize model performance and ensure production stability
· Stay updated with the latest advancements in AI/ML and GenAI ecosystems
Required Skills & Qualifications
· 4+ years of experience in Data Science / Machine Learning
· Strong programming skills in Python
· Hands-on experience with ML modeling techniques (supervised, unsupervised, NLP, etc.)
· Solid understanding of MLOps practices and tools
· Experience with MLflow or similar model lifecycle tools
· Practical experience in Generative AI (GenAI), including working with LLMs
· Experience with libraries/frameworks like Scikit-learn, TensorFlow, PyTorch
· Strong understanding of data structures, algorithms, and statistics
· Experience with cloud platforms (AWS/GCP/Azure) is a plus
Good to Have
· Experience with LLM fine-tuning, prompt engineering, or RAG pipelines
· Exposure to Docker, Kubernetes, and CI/CD pipelines
· Knowledge of data engineering workflows
AuxoAI is hiring a Senior Data Scientist with strong expertise in AI, machine learning engineering (MLE), and generative AI. You will play a leading role in designing, deploying, and scaling production-grade ML systems — including large language model (LLM)-based pipelines, AI copilots, and agentic workflows. This role is ideal for someone who thrives on balancing cutting-edge research with production rigor and loves mentoring while building impact-first AI applications.
Location - Mumbai/Bangalore/Hyderabad/Gurgaon (Hybrid - 3 Days a week in Office)
Responsibilities:
- Own the full ML lifecycle: model design, training, evaluation, deployment
- Design production-ready ML pipelines with CI/CD, testing, monitoring, and drift detection
- Fine-tune LLMs and implement retrieval-augmented generation (RAG) pipelines
- Build agentic workflows for reasoning, planning, and decision-making
- Develop both real-time and batch inference systems using Docker, Kubernetes, and Spark
- Leverage state-of-the-art architectures: transformers, diffusion models, RLHF, and multimodal pipelines
- Collaborate with product and engineering teams to integrate AI models into business applications
- Mentor junior team members and promote MLOps, scalable architecture, and responsible AI best practices
Requirements
- 5+ years of experience in designing, deploying, and scaling ML/DL systems in production
- Proficient in Python and deep learning frameworks such as PyTorch, TensorFlow, or JAX
- Experience with LLM fine-tuning, LoRA/QLoRA, vector search (Weaviate/PGVector), and RAG pipelines
- Familiarity with agent-based development (e.g., ReAct agents, function-calling, orchestration)
- Solid understanding of MLOps: Docker, Kubernetes, Spark, model registries, and deployment workflows
- Strong software engineering background with experience in testing, version control, and APIs
- Proven ability to balance innovation with scalable deployment
- B.S./M.S./Ph.D. in Computer Science, Data Science, or a related field
- Bonus: Open-source contributions, GenAI research, or applied systems at scale
The recruiter has not been active on this job recently. You may apply but please expect a delayed response.
Role & Responsibilities
Responsibilities
• Contribute to the development and optimization of enterprise-wide search systems and models.
• Design and implement algorithms to improve indexing, query relevance, and search accuracy.
• Support taxonomy, ontology, and metadata model creation for better search outcomes.
• Collaborate with business units (Loans, Insurance, Investments) to build AI-enabled search features.
• Conduct analysis of user behavior and system metrics to refine search performance.
• Work with engineers, product managers, and designers to deliver integrated search solutions.
• Develop production-grade ML systems for ranking, personalization, and recommendations.
• Participate in proof-of-concept initiatives with internal and external partners.
• Follow best practices in software engineering including CI/CD, testing, and monitoring.
• Keep abreast of emerging developments in AI/ML to apply them in practical solutions.
Ideal Candidate
Strong Data Scientist / AI Engineer / Machine Learning Engineer profiles.
Mandatory (Experience 1) – Must have minimum 5+ years of hands-on experience in Data Science, Machine Learning, Applied AI, NLP, Deep Learning, or Generative AI solutions.
Mandatory (Experience 2) – Must have strong hands-on experience in Python programming, SQL, data analysis, feature engineering, model development, and production-grade ML applications.
Mandatory (Experience 3) – Must have experience working with Machine Learning and Deep Learning frameworks such as PyTorch, TensorFlow, Keras, Scikit-learn, or equivalent.
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.
Mandatory (Experience 5) – Must have experience working with Large Language Models (LLMs) such as GPT, Llama, Mistral, Claude, Gemini, Phi, or similar foundation models.
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.
Mandatory (Experience 7) – Must have experience working with Git, CI/CD practices, production environments, and scalable AI/ML systems.
Mandatory (CTC) – The CTC breakup offered will be 75% fixed + 25% variable, as per company policy.
Mandatory (Age) - Candidate's Age should be below 30 Years
Preferred (Experience 1) – Experience with MLFlow, Kubeflow, Airflow, Prefect, Feature Stores, Model Registry, or MLOps/LLMOps frameworks.
Preferred (Experience 2) – Experience working with Vector Databases, Spark, PySpark, distributed ML pipelines, large-scale data processing, or real-time ML systems..
Preferred (Experience 3) – Familiarity with Docker, Kubernetes, Azure, AWS, GCP, cloud-native AI deployments, and scalable ML architecture.
Preferred (Company) – Candidates from AI-first startups, Fintech, Banking, Lending, Fraud Analytics, Risk Analytics, Product Companies, SaaS organizations, or data-driven technology companies.
Kindly provide the following details while sending your CV: (Mandatory details)
1) Date of Birth
2) Current Location-
3) Current CTC-
4) Expected CTC-
5) Notice Period-
6) Ready to relocate to Pune?
Regards,
The Supreme Consultancy
Website- https://lnkd.in/eawfxfxU







