8 Deepseek Jobs

Key Responsibilities: Design and Implement RAG-Based Solutions: Lead the development of a robust RAG-based system that seamlessly integrates generative AI models with retrieval mechanisms, ensuring optimal accuracy, performance, and scalability. Agent-Based Solution Development : Build AI agents that can autonomously perform tasks using information retrieval, language models, and multi-turn interactions using AutoGen, LangGraph frameworks. Generative AI Integration : Leveraging LLMs (e.g., GPT, Anthropic, Llama, Deepseek etc.) for generating high-quality, contextually accurate content in response to user queries. Prompt Engineering: Strong proficiency in prompt engineering to design, test, and optimize prompts for large language models, ensuring effective agent behavior and task completion Data & Knowledge Integration : Work on integrating structured and unstructured data sources into the RAG framework to improve model outputs. Collaborate with Teams : Work closely with product, engineering, and data science teams to ensure seamless integration of AI capabilities into broader products. Security & Compliance : Ensure following best practices in data security, privacy, and compliance, particularly in AI-driven applications. Model Evaluation : Implement strategies for continuous evaluation, monitoring, and tuning of models to ensure high-quality outputs. Data Pipeline Design : Build robust data pipelines for preprocessing and integrating structured and unstructured data sources into the platform. Collaborate with Teams : Work closely with data engineers, and software engineers to ensure seamless integration of machine learning models into production environments. Performance Optimization : Implement and experiment with various techniques such as vector search , semantic search , and knowledge distillation to enhance the platforms efficiency and accuracy. Data Quality : Ensure data quality and consistency throughout the data pipeline, implementing necessary quality checks and validation processes. Requirements: 4+ years of experience with building GenAI solutions using Python and Langchain and AutoGen technologies. Agentic AI experienced developing agents using AutoGen and LangGraph frameworks. Prior experience in building GenAI solutions using effective text representation techniques and classification algorithms. Experience with ML – Model Building, Semantic extraction techniques, data structures and modelling Experience with Supervised/Unsupervised Learning, Sentiment Analysis, Statistical Analysis using NLP and Python libraries (NLTK, Spacy, Numpy, Pandas) Experienced in building Rest API’s Experience with building applications with micro services & serverless architecture Excellent communication skills Good to have: Experience with Azure cloud services Experience with Azure Foundry & Prompt flow

Role & responsibilities Design, prototype, and deploy AI-driven applications leveraging LLMs (GPT-4, Perplexity, Claude, Gemini, etc.) and open-source transformer models. Lead or co-lead end-to-end AI/GenAI solutions : from data ingestion, entity extraction, and semantic search to user-facing interfaces. Implement RAG (Retrieval-Augmented Generation) architectures, knowledge grounding pipelines, and prompt orchestration logic. Fine-tune transformer models (BERT, RoBERTa, T5, LLaMA) on custom datasets for use cases like: Document understanding Conversational AI Question answering Summarization & Topic Modeling Integrate LLM workflows into scalable backend architectures with APIs and frontends. Work closely with business teams and pharma SMEs to translate requirements into GenAI solutions . Mentor junior engineers and contribute to AI capability development across the organization. Tech Stack & Skills Required Programming & Libraries : Python, FastAPI, LangChain, Pandas, PyTorch/TensorFlow, Transformers (HuggingFace), OpenAI SDK. Data Extraction & Processing : PDFMiner, PyMuPDF, Tabula, PyPDF2, Tesseract OCR, python-pptx. Gen AI / LLMs : OpenAI (GPT), Gemini, Perplexity, Cohere, DeepSeek, Mistral, LLaMA, BERT, RoBERTa, T5, Falcon. Use Cases : NER, Summarization, QA, Document Parsing, Clustering, Topic Modeling, QA over docs. Embedding & Vector Databases : Pinecone, FAISS, ChromaDB. RAG & Retrieval Pipelines : LangChain, Haystack, custom retrievers. Frontend/Backend Integration : React (preferred), FastAPI/Flask, REST/GraphQL APIs. Versioning & Deployment : Git, Docker, CI/CD (basic), cloud knowledge is a plus (AWS/GCP/Azure). Preferred candidate profile Degree in Computer Science, Engineering, Data Science, or related field (BE/BTech/MTech/MCA). 35 years of hands-on experience in AI/ML/NLP/LLM solution development. Strong understanding of GenAI, Prompt Engineering, LLM internals , and multi-layered data architectures. Exposure to pharma/healthcare domain is a significant plus. Excellent problem-solving skills, self-learner, and ability to work in cross-functonal teams. Experience developing new applications within an agile environment preferred. Ability to work independently and as part of a team. Exposure to MLOPs will be an added advantage.

We are hiring experienced AI Engineers for a full-time, 6-month on-premise role in Bengaluru (Electronic City) The role involves working on AI/ML solutions with open-source LLMs such as LLaMA, DeepSeek, and Mistral Strong Python programming skills, including data structures and algorithmic problem-solving, are essential Candidates must be comfortable deploying models on-premise and solving system-level challenges in Python Fine-tuning of LLMs, performance optimization, and working in Linux environments are desirable The role is hands-on and requires excellent analytical thinking and full-time office presence

You will be responsible for leading the execution of web and mobile applications for B2B and B2C clients with a focus on usability, agility, and AI-powered delivery. As a Technical Project Coordinator, you will serve as the main bridge between clients and internal teams, translating client needs into actionable plans, and leading project planning, sprints, timelines, and delivery workflows. Your role will involve ensuring UX and usability are embedded throughout the product lifecycle, supporting developers with technical clarity, and identifying opportunities to integrate AI into the development process and final product. You should have a strong understanding of UX principles and user behavior, as well as experience working with AI-powered productivity tools. While you are not required to write code, you should be fluent in technologies such as Next.js, React, Python (Django), Node.js, Flutter, AWS, and AI/Dev Tools like GPT APIs, Cursor, DeepSeek, and n8n. Your responsibilities will include keeping deliverables on track with scope, KPIs, and deadlines, from project kickoff to post-launch iterations. The ideal candidate for this role will have at least 4-8 years of hands-on experience in coordinating digital product builds, a proven track record of delivering complex web/mobile products end-to-end, and excellent communication, problem-solving, and decision-making skills. You should be comfortable discussing APIs, data structures, and development lifecycles, and be agile, resourceful, and committed to rapid, high-quality execution. Bonus points will be awarded if you have experience with AI integration in products, working in a fast-paced agency or startup environment, and an understanding of client expectations in the UAE/Saudi digital landscape.,

Key Responsibilities: LLM Deployment & Optimization Deploy, fine-tune, and optimize open-source LLMs (e.g., LLaMA, Mistral, CodeS, DeepSeek). Implement quantization (e.g., 4-bit, 8-bit) and pruning for efficient inference on commodity hardware. Build and manage inference APIs (REST/gRPC) for production use. Infrastructure Management Set up and manage on-premise GPU servers and VM-based deployments. Build scalable cloud-based LLM infrastructure using AWS (SageMaker, EC2), Azure ML, or GCP Vertex AI. Ensure cost efficiency by choosing appropriate hardware and job scheduling strategies. MLOps & Reliability Engineering Develop CI/CD pipelines for model training, testing, evaluation, and deployment. Integrate version control for models, data, and hyperparameters. Set up logging, tracing, and monitoring tools (e.g., MLflow, Prometheus, Grafana) for model performance and failure detection. Security, Compliance & Performance Ensure data privacy (FERPA/GDPR) and enforce security best practices across deployments. Apply secure coding standards and implement RBAC, encryption, and network hardening for cloud/on-prem. Cross-functional Integration Work closely with AI solution engineers, backend developers, and product owners to integrate LLM services into the platform. Support performance benchmarking and A/B testing of AI features across modules. Documentation & Internal Enablement Document LLM pipelines, configuration steps, and infrastructure setup in internal playbooks. Create guides and reusable templates for future deployments and models. Key Requirements: Education: Bachelors or Masters in Computer Science, AI/ML, Data Engineering, or related field. Technical Skills: Strong Python experience with ML libraries (e.g., PyTorch, Hugging Face Transformers). Familiar with LangChain, LlamaIndex, or other RAG frameworks. Experience with Docker, Kubernetes, and API gateways (e.g., Kong, NGINX). Working knowledge of vector databases (FAISS, Pinecone, Qdrant). Familiarity with GPU deployment tools (CUDA, Triton Inference Server, HuggingFace Accelerate). Experience: 4+ years in an AI/MLOps role, including experience in LLM fine-tuning and deployment. Hands-on work with model inference in production environments (both cloud and on-prem). Exposure to SaaS and modular product environments is a plus.

Role & responsibilities The AI/ML Engineer will be responsible for the development and implementation of open-source large language models (LLM) tailored for the Banking, Financial Services, and Insurance (BFSI) sector. You will work collaboratively with cross-functional teams to design innovative solutions that enhance our product offerings, enabling more efficient customer interactions and data insights. Your analytical skills will help in improving the performance and scalability of LLM applications while ensuring adherence to compliance and security standards. Responsibilities Develop and implement open-source LLMs for BFSI applications. Collaborate with product managers, data scientists, and software engineers to define project objectives and deliver high-quality solutions. Conduct experiments and optimize model performance using real-world datasets. Monitor and evaluate model effectiveness in production and refine models based on feedback. Stay up-to-date with the latest advancements in AI/ML to incorporate relevant best practices into the development process. Contribute to documentation and knowledge base for models and methodologies. Requirements Bachelors degree or equivalent experience in Computer Science, Engineering, or a related field. Minimum of 3+ years of experience in AI/ML development, preferably in the BFSI industry, [With hands on coding and interview will be technical, you need to demonstrate your expertise in coding without AI agents and search engine You must have built and deployed AI/ML solutions to production Proficient in programming languages such as Python and also preferably typescript and java ; Python is core requirement . Proficiency in flask,fast api framework and have built application which is compliant to security standards and performant and scalable Able to work with rdbms and nosql databases and vector databases Experience with open-source ML frameworks (e.g., TensorFlow, PyTorch). Industry experience with open-source LLM frameworks (e.g., Langchain, ollama etc...). Solid understanding of machine learning algorithms, data structures, and statistical methods. Familiarity with data preprocessing, feature engineering, and model evaluation techniques. Excellent problem-solving skills and ability to work in a fast-paced environment. Strong communication skills to convey complex technical concepts to non-technical stakeholders

Seeking a dynamic BDE to generate leads, pitch services, and build client relationships. Must have strong communication skills, 624 months of experience, and a passion for sales and growth in the digital/IT space.

We are looking for AI-Project manager who have good experience in market intelligence firm specializing in industry analysis, forecasting, and custom market research. Role & responsibilities Project management talent Strong communication skills Fluency in all AI topics and models Technical skill to download Mistral, Deepseek and other AI apps and customize them internal use and for custom projects for our customers. Highly presentable for customer and prospect presentations custom AI market research services Fluency with Chat GPT's AI-generated coding app "Coding Assistant" Preferred candidate profile Excellent communication skill. Full -time Remote opportunity.