AI/ML Engineer – Production AI, LLM Systems

This is a fully remote position, open to applicants in India.

📋 Description

• Design, create, and implement AI systems, including large language models (LLMs), retrieval-augmented generation (RAG), agentic workflows, and machine learning/deep learning (ML/DL) solutions.

• Choose models and architectures while considering accuracy, latency, cost, and complexity.

• Train and fine-tune models utilizing PyTorch or Keras, focusing on data preparation and assessment.

• Execute and evaluate research methodologies prior to implementation.

• Develop APIs, inference pipelines, and backend integrations.

• Take responsibility for evaluating metrics and monitoring quality, latency, and cost.

• Oversee, troubleshoot, and enhance AI systems post-launch.

• Ensure readiness for production and identify regressions before they affect users.

• Collaborate with software engineers and product teams to embed AI into applications.

• Engage in technical discussions and contribute to decision-making.

• Document architecture, implementation strategies, and significant technical choices.

• Review and analyze machine learning research papers.

• Apply promising methodologies and replicate results when relevant.

• Adapt novel techniques into systems ready for production.

• Contribute to ongoing innovation in AI and engineering projects.

• Work alongside engineering leadership, product teams, software engineers, backend developers, and global AI research and development groups.

⛳️ Requirements

• A minimum of 3 years of practical AI/ML engineering experience, with at least one system deployed in a production environment.

• Solid understanding of natural language processing (NLP) fundamentals, such as tokenization, embeddings, classification, named entity recognition (NER), and information extraction.

• Strong engineering capabilities in coding, Git, testing, API/system design, and debugging.

• Direct experience in model training using PyTorch or Keras.

• Familiarity with generative model architectures, including Transformers and Variational Autoencoders (VAEs).

• Production experience with LLMs, including retrieval-augmented generation (RAG), embeddings/vector databases, and prompt/evaluation design.

• Experience with FastAPI or similar frameworks, Docker, and at least one cloud service platform such as AWS, GCP, or Azure.

• Capability to read machine learning research papers and convert concepts into functional code.

• Experience in fine-tuning LLMs, including Low-Rank Adaptation (LoRA) and reinforcement learning-based methods.

• Knowledge of SQL databases.

• Familiarity with agent frameworks such as LangGraph or LangChain.

• Experience with Kubernetes, Continuous Integration/Continuous Deployment (CI/CD), and model-serving infrastructure.

• Contributions to open-source projects or experience in reproducing research results.

🏝️ Benefits

• Annual compensation ranging from ₹15,00,000 to ₹22,00,000 (15–22 LPA), depending on experience and technical proficiency.

• Contract and payment management facilitated through Deel.

• A 90-day probationary period.

• Eligibility for benefits upon successful completion of the probation period.

• Paid Time Off (PTO) in line with company policy.

• Holiday pay for company-recognized holidays.

• Opportunities for career advancement and professional development.