Artificial Intelligence/Machine Learning Engineer Python/LLM

Job description

<p><p><b>Position :</b> AI ML Engineer</p><br/><p><b>Experience :</b> 7+ years in Python development with proven experience in AI and productivity tooling</p><br/><p><b>Work mode :</b> Hybrid/Remote</p><br/><p><b>NP :</b> Immediate joiners</p><br/><p><b>Job Mode :</b> Contract(6 months+ extendable)</p><br/><p><b>Working hours :</b> 2pm - 12pm IST</p><br/><p><b>Job Summary :</b></p><br/><p>We are seeking a Senior Python Developer who excels at building scalable, AI-integrated systems using modern tools and frameworks.

</p><p><br/></p><p>The ideal candidate embraces AI-assisted development (GitHub Copilot, ChatGPT, AutoGen, etc.) to boost productivity, improve code quality, and drive innovation across our application stack.

</p><p><br/></p><p>This role combines backend expertise, cloud-native architecture, and hands-on AI integration to deliver intelligent, high-performance solutions.</p><br/><p><b>Key Responsibilities :</b></p><br/><p><b>AI Model Integration & Optimization :</b></p><br/><p>- Integrate APIs from multiple AI platforms (OpenAI, Anthropic, Gemini, Llama, Mistral, etc.) into scalable backend systems.</p><br/><p>- Build multi-model orchestration layers balancing cost, latency, and accuracy.</p><br/><p>- Fine-tune prompts, manage context windows, and implement RAG (Retrieval-Augmented Generation) solutions for domain-specific use cases.</p><br/><p>- Optimize token usage, caching, and filtering strategies to enhance system efficiency and user experience.</p><br/><p><b>Application & System Development :</b></p><br/><p>- Design and implement AI-enabled workflows seamlessly integrated with web, mobile, or enterprise ecosystems.</p><br/><p>- Develop Python-based backends and APIs using frameworks like FastAPI, Flask, or Django.</p><br/><p>- Build and deploy microservices and cloud-native services leveraging Docker, Kubernetes, and serverless architectures</p><br/><p>- Collaborate with frontend, DevOps, and product teams to ensure smooth feature delivery and deployment.</p><br/><p>- Monitor and evaluate AI responses through metrics, evaluation frameworks, or RLHF-inspired feedback loops.</p><br/><p>- Implement AI guardrails for responsible usage including bias detection, toxicity filtering, and compliance enforcement.</p><br/><p>- Debug and resolve performance or reliability issues in AI-powered production systems.</p><br/><p><b>Innovation & Collaboration :</b></p><br/><p>- Stay up to date with the evolving AI model landscape, exploring new models, APIs, and orchestration frameworks.</p><br/><p>- Experiment with multi-modal AI (vision, text, speech) for applicability in client scenarios.</p><br/><p>- Work closely with cross-functional teams to translate business goals into intelligent, automated features.</p><br/><p><b>Primary Skills :</b></p><br/><p>- Python backend expert : FastAPI, async I/O, API design, testing.</p><br/><p>- Production LLM integration : OpenAI/Anthropic/Gemini/Mistral; prompt and context strategies; RAG with a vector DB.</p><br/><p>- Cloud-native delivery : Docker, AWS (preferred), CI/CD, IaC basics (Terraform or Pulumi).</p><br/><p>- Data layer : SQL (PostgreSQL), caching/queues (Redis + Celery/RQ/SQS/Kafka).</p><br/><p>- Daily AI-assisted development (Copilot/Others) for coding and tests.</p><br/><p><b>Required Skills & Qualifications :</b></p><br/><p>- Expert in Python backend development with hands-on experience integrating AI models, building cloud-native microservices, and using AI-assisted coding tools for faster, smarter development.</p><br/><p>- Proven hands-on experience integrating LLM APIs (OpenAI, Claude, Gemini, Llama, etc.).</p><br/><p>- Strong expertise in AI/ML frameworks (TensorFlow, PyTorch, scikit-learn, Hugging Face, etc.)" as essential qualification</p><br/><p>- Practical knowledge of LangChain, LlamaIndex, Codium or similar frameworks for AI workflow orchestration.</p><br/><p>- Understanding of prompt engineering, embeddings, vector databases (Pinecone, Weaviate, FAISS, pgvector), and RAG pipelines.</p><br/><p>- Strong background in cloud platforms (AWS, GCP, Azure), containerization, and orchestration.</p><br/><p>- Deep understanding of REST/GraphQL APIs, async programming, task queues, and caching mechanisms.</p><br/><p>- Familiarity with SQL/NoSQL databases (PostgreSQL, MongoDB, Redis).</p><br/><p>- Experience using AI-assisted tools such as GitHub Copilot, ChatGPT API, AutoGen, or OpenDevin for coding and testing automation.</p><br/><p>- Exposure to CI/CD pipelines and Infrastructure as Code (Terraform, Pulumi).</p><br/><p>- Knowledge of data preprocessing, NLP/NLU, and model evaluation techniques.</p><br/><p>- Data Engineering & Processing, Data pipeline development , ETL/ELT processes, Batch processing and stream processing frameworks, Large-scale data handling with pandas, NumPy, Dask</p><br/></p> (ref:hirist.tech)

Required Skill Profession

Computer Occupations