Tier 1 college only Associate Lead - AI/ML Engineer ( Python, AL/ML at Staffnixcom · Pune · 3 - 6 years · ₹21L - ₹32L / yr · Bootstrapped · Posted 18 Aug 2026

Tier 1 college only Associate Lead - AI/ML Engineer ( Python, AL/ML
at Staffnixcom
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
11
Preferred (Experience 1) – Experience with MLFlow, Kubeflow, Airflow, Prefect, Feature Stores, Model Registry, or MLOps/LLMOps frameworks.
12
Preferred (Experience 2) – Experience working with Vector Databases, Spark, PySpark, distributed ML pipelines, large-scale data processing, or real-time ML systems..
13
Preferred (Experience 3) – Familiarity with Docker, Kubernetes, Azure, AWS, GCP, cloud-native AI deployments, and scalable ML architecture.
14
Preferred (Company) – Candidates from AI-first startups, Fintech, Banking, Lending, Fraud Analytics, Risk Analytics, Product Companies, SaaS organizations, or data-driven technology companies
15
Mandatory ( Pedigree) - B.TECH / M.TECH from Tier 1 Colleges (IIT's, NIT's, BITS) are Considered.

Similar jobs (10)
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
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.
🚀 WE’RE HIRING | AI/ML GENERATIVE AI ENGINEER
📍 Location: Remote
💼 Experience: 5+ Years
🔄 Position: Contract – Extendable
🔹 ROLE HIGHLIGHTS
➤ Build and deploy AI/ML amp; Generative AI solutions
➤ Develop LLM, RAG, NLP, Recommendation amp; Predictive solutions
➤ Work on AI Agents, Chatbots, Computer Vision amp; Content Intelligence
➤ Build ML models using PyTorch, TensorFlow, Keras amp; Scikit-learn
➤ Develop RAG solutions using LangChain, LlamaIndex, FAISS/Milvus
➤ Integrate OpenAI, Azure OpenAI, AWS Bedrock, Vertex AI amp; Hugging Face
➤ Build scalable AI APIs using Python, FastAPI/Flask/Django
➤ Contribute to Private AI amp; Smart Agentic Systems
⚙️ MUST-HAVE SKILLS
◆ Python – 3+ years
◆ AI/ML – 5+ years
◆ Generative AI – 2+ years
◆ LLMs, RAG, Embeddings , Transformers
◆ ML/DL, NLP amp; Predictive Analytics
◆ Cloud AI Platforms – Azure / AWS / GCP
◆ AI/ML Deployment | MLOps
Interview Process - F2F Round at Pune Location
Job Description – Python & Generative AI Engineer
Python & Generative AI Engineer
Location: Bangalore, India
Experience: 4+ Years
Employment Type: Full-time
Job Summary
We are looking for an experienced Python & Generative AI Engineer with 4+ years of software development experience and strong hands-on expertise in Python, LLMs, Generative AI, and AI application development.
The ideal candidate should be comfortable building production-grade AI solutions, integrating LLMs with enterprise applications, and developing scalable APIs and services using Python.
Key Responsibilities
- Design, develop, and deploy Generative AI applications using Python and modern AI/ML frameworks.
- Work with Large Language Models (LLMs) such as GPT, Claude, Gemini, Llama, or similar models.
- Develop RAG (Retrieval-Augmented Generation) pipelines using vector databases and embedding models.
- Build AI-powered applications using frameworks such as LangChain, LangGraph, LlamaIndex, or equivalent.
- Develop scalable REST APIs and backend services using FastAPI, Flask, or Django.
- Integrate LLM APIs, prompt engineering, function/tool calling, and structured outputs into enterprise applications.
- Work with vector databases such as FAISS, Pinecone, Weaviate, Milvus, or Azure AI Search.
- Implement document processing, chunking, embeddings, semantic search, and knowledge retrieval solutions.
- Evaluate LLM responses for accuracy, relevance, hallucination, latency, and cost.
- Build and maintain production-ready AI pipelines with appropriate monitoring, logging, security, and error handling.
- Collaborate with data scientists, ML engineers, software engineers, and business stakeholders to deliver AI solutions.
- Write clean, reusable, testable, and well-documented Python code.
- Participate in architecture discussions, code reviews, testing, deployment, and production support.
Required Skills
- 4+ years of experience in software/Python development.
- Strong proficiency in Python and object-oriented programming.
- Hands-on experience with Generative AI and LLM-based applications.
- Experience with OpenAI/Azure OpenAI, Anthropic, Google Gemini, or open-source LLMs.
- Strong understanding of Prompt Engineering and LLM application patterns.
- Experience implementing RAG pipelines.
- Knowledge of embeddings, vector databases, semantic search, and document retrieval.
- Experience with LangChain, LangGraph, LlamaIndex, or similar frameworks.
- Strong experience developing REST APIs using FastAPI/Flask/Django.
- Familiarity with Git, CI/CD, Docker, and cloud platforms such as AWS, Azure, or GCP.
- Good understanding of SQL and databases.
- Strong problem-solving and communication skills.
Good to Have
- Experience with AI agents / Agentic AI and tool/function calling.
- Experience with multi-agent frameworks.
- Knowledge of MLOps/LLMOps and model evaluation.
- Experience with Kubernetes and containerized deployments.
- Knowledge of NLP, machine learning, or deep learning.
- Experience with Azure AI, AWS Bedrock, Amazon SageMaker, or Google Vertex AI.
- Understanding of responsible AI, data privacy, and LLM security.
Education
Bachelor's or Master's degree in Computer Science, Information Technology, Engineering, or a related field.

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
- Senior Machine Learning Engineer – Vertex AI
- Senior Generative AI Engineer – GCP
- Google Cloud AI/ML Engineer
- MLOps Engineer – Vertex AI
- LLM Engineer – RAG, Gemini, and Vertex AI
Roles & Responsibilities
- Design and develop intelligent AI-based applications using advanced NLP and LLM techniques to solve real-world business challenges in financial services.
- Build and optimize Retrieval-Augmented Generation (RAG) pipelines leveraging structured and unstructured financial data.
- Integrate and orchestrate LLMs/SLMs for question-answering, summarization, semantic search, and document understanding.
- Develop and maintain RESTful APIs (sync and async) to serve NLP models and chatbot interfaces using frameworks like FastAPI, Flask, etc.
- Should have knowledge of advanced prompting techniques.
- Implement semantic search, hybrid search, and text retrieval systems using Elasticsearch and vector databases (e.g., FAISS, Pinecone, Weaviate).
- Perform NLP tasks such as entity recognition, text classification, intent detection, embedding generation, and sentiment analysis where required.
- Monitor and fine-tune LLM/SLM performance with real-world user data to improve relevance, latency, and accuracy.
- Exposure to LLMOps tools for monitoring, evaluation, and versioning of AI models in production.
- Build, train, and evaluate deep learning models for NLP tasks including classification, NER, summarization, and embedding generation.
- Develop traditional machine learning models (e.g., regression, decision trees, clustering) for structured data analysis and prediction tasks.
- Interact with cross-functional teams to understand system issues and follow up with respective teams to get them fixed.
- Understand and identify areas of improvement across businesses and participate in solution identification and implementation.
- Should be able to work as an Individual Contributor on new and existing projects.
- Positive and problem-solving attitude, must work as an independent contributor.
Ideal Candidate
1.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.
13.Preferred (Experience 3) - Experience working with PostgreSQL, MongoDB, Redis, Kafka, or large-scale data platforms.
14.Preferred (Experience 4) - Familiarity with Docker, Kubernetes, cloud platforms, and scalable deployment architecture.
15.Preferred (Company) - Candidates from AI-first startups, product companies, SaaS organizations, fintech, or data-driven technology companies.
16.Mandatory ( Age ) - Candidate Should be Below 28 Years.
17.Mandatory ( Pedigree) - B.TECH / M.TECH from Tier 1 Colleges (IIT's, NIT's, BITS) are Considered.
Experience - 4 to 6 year
Location – Ahmedabad/Pune/Indore
- Additional Job Description
Additional Job Description
Required Skills and Experience:
- Strong proficiency in Python and experience with ML/AI libraries (scikit-learn, TensorFlow, PyTorch, Hugging Face ecosystem).
- Hands-on experience with LLMs, RAG, vector databases, and retrieval pipelines.
- Practical experience deploying agentic workflows and building multi-step, tool-enabled agents.
- Experience using Garak (or similar LLM red-teaming/vulnerability scanners) to identify model weaknesses and harden deployments.
- Demonstrated experience implementing content filtering / moderation systems.
- Solid skills working with structured and unstructured data and advanced feature engineering.
- Familiarity with cloud GenAI platforms and services (Azure AI Services preferred; AWS/GCP acceptable).
- Experience building APIs/microservices; containerization (Docker), orchestration (Kubernetes).
- Strong understanding of model evaluation, performance profiling, inference cost optimization, and observability.
- Good knowledge of security, data governance, and privacy best practices for AI 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
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









