AI/ML Engineer

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

📋 Description

• Design, develop, train, fine-tune, and assess machine learning and LLM-based solutions.

• Construct and maintain comprehensive ML/AI pipelines that encompass data ingestion, processing, model development, inference, deployment, and monitoring.

• Create and implement Generative AI applications, including LLM-driven solutions and RAG-based systems.

• Utilize prompt engineering, context engineering, and LLM fine-tuning techniques to enhance model performance and reliability.

• Design and execute solutions leveraging vector databases, embeddings, and RAG architectures.

• Collaborate with Solution Architects, Data Scientists, and engineering teams to convert business needs into scalable AI/ML solutions.

• Optimize models and AI applications for accuracy, latency, scalability, and cost efficiency.

• Establish model evaluation, guardrails, observability, and monitoring for production AI/ML systems.

• Adhere to MLOps best practices, including model versioning, CI/CD, deployment automation, and model lifecycle management.

• Keep updated with advancements in Generative AI, LLMs, AI engineering, and machine learning technologies.

⛳️ Requirements

• 3–6 years of practical experience in Machine Learning Engineering or a closely related field.

• Strong expertise in Python.

• Proficiency with PyTorch, TensorFlow, and scikit-learn.

• Hands-on experience with Generative AI and LLM-based applications.

• Experience in LLM fine-tuning, prompt engineering, and context engineering.

• Solid understanding of RAG architectures, embeddings, vector databases, and semantic search.

• Experience in building and deploying production-quality ML/AI pipelines.

• Familiarity with MLOps practices, including model versioning and CI/CD for machine learning workloads.

• Experience with at least one leading cloud-based ML platform: AWS SageMaker, Azure Machine Learning, or Google Cloud Vertex AI.

• Strong knowledge of model evaluation, performance optimization, and production monitoring.

• Ability to translate business needs into actionable AI/ML solutions.

• Experience in AI/ML solutions within regulated or highly sensitive domains, such as healthcare or government technology (preferred).

• Experience with multi-agent AI systems and orchestration frameworks (preferred).

• Familiarity with LLM evaluation frameworks and AI observability tools (preferred).

• Knowledge of Docker and Kubernetes (preferred).

• Experience with APIs, microservices, and scalable AI application architectures (preferred).

• Strong problem-solving and communication abilities.

• Capability to work efficiently in a dynamic, collaborative environment.

🏝️ Benefits

• Advanced training opportunities.

• Chance to implement advanced training in real-world business solutions.

• Flexible remote work arrangement.

• Contract role.