Lead Data Scientist at Tekdi Technologies Pvt. Ltd. · Pune · 6 - 8 years · Profitable · Posted 5 Sep 2025
Machine Learning (ML)We are seeking a highly skilled Senior/Lead Data Scientist with deep expertise in AI/ML/Gen AI, including Deep Learning, Computer Vision, and NLP. The ideal candidate will bring strong hands-on experience, particularly in building, fine-tuning, and deploying models, and will work directly with customers with minimal supervision.
This role requires someone who can not only lead and execute technical projects but also actively contribute to business development through customer interaction, proposal building, and RFP responses. You will be expected to take ownership of AI project execution and team leadership, while helping Tekdi expand its AI footprint.
Key Responsibilities:
Contribute to AI business growth by working on RFPs, proposals, and solutioning activities.
- Lead the team in delivering customer requirements, ensuring quality and timely execution.
Develop and fine tune advanced AI/ML models using deep learning and generative AI techniques.
- Fine-tune and optimize Large Language Models (LLMs) such as GPT, BERT, T5, and LLaMA.
- Interact directly with customers to understand their business needs and provide AI-driven solutions.
- Work with Deep Learning architectures including CNNs, RNNs, and Transformer-based models.
- Leverage NLP techniques such as summarization, NER, sentiment analysis, and embeddings.
- Implement MLOps pipelines and deploy scalable AI solutions in cloud environments (AWS, GCP, Azure).
- Collaborate with cross-functional teams to integrate AI into business applications.
- Stay updated with AI/ML research and integrate new techniques into projects.
Required Skills & Qualifications:
- Minimum 6 years of experience in AI/ML/Gen AI, with at least 3+ years in Deep Learning/Computer Vision.
- Strong proficiency in Python and popular AI/ML frameworks (TensorFlow, PyTorch, Hugging Face, Scikit-learn).
- Hands-on experience with LLMs and generative models (e.g., GPT, Stable Diffusion).
- Experience with data preprocessing, feature engineering, and performance evaluation.
- Exposure to containerization and cloud deployment using Docker, Kubernetes.
- Experience with vector databases and RAG-based architectures.
- Ability to lead teams and projects, and work independently with minimal guidance.
- Experience with customer-facing roles, proposals, and solutioning.
Educational Requirements:
- Bachelor’s, Master’s, or PhD in Computer Science, Artificial Intelligence, Information Technology, or related field.
Preferred Skills (Good to Have):
- Knowledge of Reinforcement Learning (e.g., RLHF), multi-modal AI, or time-series forecasting.
- Familiarity with Graph Neural Networks (GNNs).
- Exposure to Responsible AI (RAI), AI Ethics, or AutoML platforms.
- Contributions to open-source AI projects or publications in peer-reviewed journals.
Shubham Vishwakarma
Full Stack Developer - Averlon
About Tekdi Technologies Pvt. Ltd.
About
Tekdi Technologies is a leading IT Solutions provider focusing on delivering enterprise-class, end-to-end solutions for businesses & individuals in a wide array of verticals. It offers a dynamic portfolio of digital solutions, products, platforms, and services that bring greater choice, faster time to market, and flexibility to its customers. We leverage Open Source Technologies to deliver cutting-edge solutions driven by a combination of robust strategies, passionate teams, and a global culture rooted in innovation and automation. Our experience, coupled with the use of Open Source gives you the advantage of cost-effective, secure, and up-to-date solutions.
Company social profiles
Similar jobs (10)
Data ScienceStrong 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.
The recruiter has not been active on this job recently. You may apply but please expect a delayed response.
Data ScienceStrong 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.
The recruiter has not been active on this job recently. You may apply but please expect a delayed response.
Data ScienceStrong 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.
The recruiter has not been active on this job recently. You may apply but please expect a delayed response.
Machine Learning (ML)
PythonStrong AI Engineer / Machine Learning Engineer profiles.
2
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.
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 30 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.
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
The recruiter has not been active on this job recently. You may apply but please expect a delayed response.
Data ScienceMachine Learning (ML)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 30 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.
The recruiter has not been active on this job recently. You may apply but please expect a delayed response.
PythonStrong 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.
Data SciencePython🚨 Hiring – Data Scientist | Python + Agentic AI
💼 Experience: 5+ Years
Must Have:
• Strong Data Science experience
• Python
• Agentic AI / AI Agents
• Generative AI / LLMs
• RAG / Vector Databases
• LangChain / LangGraph or similar Agent Frameworks
• Machine Learning & NLP
About the Role:
We are looking for an ideal candidate with 5+ years of experience in Data Science / Machine Learning, with strong hands-on experience in Generative AI, Large Language Models (LLMs), NLP, and AI-powered applications. The candidate should be comfortable working across the complete AI lifecycle—from understanding business requirements and experimenting with models to building, evaluating, deploying, and monitoring production-grade GenAI solutions.
The role requires a combination of strong technical expertise, business understanding, problem-solving ability, and stakeholder management skills.
Key Responsibilities:
Generative AI & LLM
· Design, develop, and deploy Generative AI and LLM-based solutions for enterprise use cases.
· Work with models such as OpenAI, Azure OpenAI, Llama, Mistral, Gemini, or equivalent LLM platforms.
· Develop applications using prompt engineering, structured outputs, function/tool calling, and LLM orchestration.
· Design and implement Retrieval-Augmented Generation (RAG) solutions.
· Work with vector databases and semantic search for enterprise knowledge retrieval.
· Develop and evaluate AI agents and multi-step AI workflows.
· Implement techniques such as prompt optimization, context management, grounding, and hallucination reduction.
· Develop AI solutions for text classification, summarization, information extraction, question answering, document intelligence, and other enterprise use cases.
Machine Learning & Data Science
· Develop and optimize traditional Machine Learning and statistical models where appropriate.
· Perform data exploration, feature engineering, model selection, training, validation, and evaluation.
· Apply appropriate ML and statistical techniques to solve business problems.
· Work with structured, unstructured, and semi-structured data.
· Develop scalable data pipelines to support AI/ML solutions.
· Collaborate with Data Engineers to prepare and manage data for AI applications.
AI Evaluation & Productionization
· Design evaluation frameworks to measure LLM accuracy, relevance, groundedness, toxicity, latency, and cost.
· Implement guardrails and responsible AI practices.
· Monitor model and application performance in production.
· Identify model/data drift and implement appropriate improvement strategies.
· Optimize AI solutions for performance, scalability, reliability, and cost.
· Support deployment and productionization of AI/ML solutions.
· Client & Delivery Responsibilities
· Work closely with the CEO, Delivery team, Solution Architects, Engineering teams, and clients to understand business problems and identify AI opportunities.
· Translate business requirements into practical AI/ML solutions.
· Participate in client discussions, solution presentations, technical workshops, and POCs.
· Develop rapid prototypes and demonstrate the feasibility of GenAI solutions.
· Convert successful POCs into scalable, production-ready applications.
· Provide technical guidance and contribute to AI solution architecture.
· Prepare technical documentation, solution approaches, and project estimates where required.
· Stay current with developments in Generative AI, LLMs, Agentic AI, and AI engineering.
Required Skills:
· 5+ years of hands-on experience in Data Science, Machine Learning, AI, or a related field.
· Strong practical experience in Generative AI and LLM-based applications.
· Strong proficiency in Python.
· Strong understanding of Machine Learning and statistical concepts.
· Hands-on experience with:
o LLMs
o Prompt Engineering
o RAG
o Vector Databases
o Embeddings
o Semantic Search
o LLM Evaluation
o AI Guardrails
· Experience with frameworks/tools such as LangChain, LangGraph, LlamaIndex, or equivalent.
· Experience with APIs and integrating LLMs into enterprise applications.
· Strong SQL and data handling skills.
· Experience working with large and complex datasets.
· Strong understanding of NLP concepts.XX
Technical Skills:
· Experience with OpenAI / Azure OpenAI / AWS Bedrock / Google Vertex AI.
· Experience with vector databases such as Pinecone, Weaviate, Milvus, FAISS, or equivalent.
· Experience with Databricks, Snowflake, or cloud data platforms.
· Experience with Docker and CI/CD.
· Exposure to AWS, Azure, or GCP.
· Experience with ML/AI deployment and MLOps.
· Knowledge of AI security, data privacy, governance, and responsible AI.
· Experience building AI Agents / Agentic AI workflows.
· Experience with multimodal AI is an added advantage
Key Competencies
· Strong analytical and problem-solving ability.
· Ability to translate business problems into practical AI solutions.
· Strong communication and presentation skills.
· Ability to interact confidently with senior stakeholders and clients.
· Strong ownership and delivery mindset.
· Ability to work independently in a fast-paced environment.
- Strong experimentation and innovation mindset.
- Ability to balance technical feasibility, business value, scalability, and cost.
Required Education & Experience:
· Bachelor's or Master's degree in Computer Science, Data Science, Artificial Intelligence, Statistics, Mathematics, Engineering, or a related discipline
Machine Learning (ML)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.
Follow CutshortShubham Vishwakarma
Full Stack Developer - Averlon