AI/ML Engineer
GeMTech PARAS
Job Description
Company Description Gemtech PARAS is an AI RFP analysis and bid execution platform.
It helps teams understand complex RFPs faster by turning long documents into clear summaries, requirements, and checklists. It organizes tasks, processes, documents, and deadlines in one place so teams can work in a structured way. It also automates compliant submission preparation, reducing manual effort, errors, and follow-up.
In simple terms, it helps businesses move from RFP discovery to submission with more speed, clarity, and control. The platform is uniquely engineered to optimize how organizations discover, evaluate, and secure complex public and private sector contracts.
- Role Description
We’re looking for a powerhouse AI/ML Engineer to turn cutting-edge research into production-ready reality. You won't just be building prototypes; you’ll be designing, deploying, and scaling GenAI systems that solve real business problems. If you live at the intersection of robust software engineering and advanced machine learning, let’s talk.
Technical Expertise
· GenAI & Orchestration: Expert-level development using Lang Chain and Lang Graph; specialized in multi-step RAG, agentic workflows, and tool-augmented chains.
· NLP & Text Processing: Mastery of document parsing, chunking strategies, embeddings, and retrieval optimization.
· Core Engineering: Advanced Python (NumPy, Pandas, scikit-learn, PyTorch/TensorFlow) and backend service development using FastAPI.
· Vector Infrastructure: Proven experience building and maintaining pipelines with FAISS, AWS Open Search, or similar vector databases.
· Cloud Ecosystems (Mandatory): High proficiency in either AWS (SageMaker, Lambda, ECS, Step Functions) or Azure (Azure OpenAI, Functions, App Services).
· MLOps & DevOps: Strong grasp of the ML lifecycle—monitoring, versioning (MLflow), and CI/CD pipelines (Jenkins, GitHub Actions).
How You’ll Make an Impact
- Design & Own: Lead end-to-end ML/GenAI workflows, from data ingestion and preprocessing to deployment and inference.
- Build Production Systems: Architect robust GenAI systems including API design, data pipelines, and scalable monitoring.
- Optimize Everything: Continuously evaluate and refine prompts, chains, and agents to improve accuracy while balancing latency and cost efficiency.
- Collaborate & Integrate: Partner with cross-functional teams to weave AI capabilities into dynamic applications for seamless user experiences.
- Ensure Excellence: Write high-quality, testable code and conduct rigorous unit/integration testing to ensure system reliability.
- Diagnose & Scale: Resolve complex performance and reliability issues across diverse environments.
What You Bring
- Experience: 4+ years of professional experience as an AI, ML, or Software Engineer, specifically building production-grade applications.
- Education: Bachelor’s degree in Computer Science, Information Technology, or Software Engineering.
- Engineering Rigor: A strong software background with experience in version control (Git) and Agile development.
- Problem Solving: A sharp analytical mind with the communication skills to align technical solutions with business goals.