AI/ML Engineer

• Design, develop, train, fine-tune, and evaluate machine learning and LLM-based solutions
• Build and maintain end-to-end ML/AI pipelines covering data ingestion, processing, model development, inference, deployment, and monitoring
• Develop and implement Generative AI applications, including LLM-powered solutions and RAG-based systems
• Apply prompt engineering, context engineering, and LLM fine-tuning techniques to improve model performance and reliability
• Design and implement solutions using vector databases, embeddings, and RAG architectures
• Collaborate with Solution Architects, Data Scientists, and engineering teams to translate business requirements into scalable AI/ML solutions
• Optimize models and AI applications for accuracy, latency, scalability, and cost efficiency
• Implement model evaluation, guardrails, observability, and monitoring for production AI/ML systems
• Follow MLOps best practices, including model versioning, CI/CD, deployment automation, and model lifecycle management
• Stay current with developments in Generative AI, LLMs, AI engineering, and machine learning technologies

• 3–6 years of hands-on experience in Machine Learning Engineering or a closely related role
• Strong proficiency in Python
• Experience with PyTorch, TensorFlow, and scikit-learn
• Hands-on experience with Generative AI and LLM-based applications
• Experience with LLM fine-tuning, prompt engineering, and context engineering
• Strong understanding of RAG architectures, embeddings, vector databases, and semantic search
• Experience building and deploying production-grade ML/AI pipelines
• Working knowledge of MLOps practices, including model versioning and CI/CD for machine learning workloads
• Experience with at least one major cloud-based ML platform: AWS SageMaker, Azure Machine Learning, or Google Cloud Vertex AI
• Strong understanding of model evaluation, performance optimization, and production monitoring
• Ability to translate business requirements into practical AI/ML solutions
• Experience working on AI/ML solutions in regulated or highly sensitive domains, such as healthcare or government technology (nice to have)
• Experience with multi-agent AI systems and orchestration frameworks (nice to have)
• Experience with LLM evaluation frameworks and AI observability tools (nice to have)
• Familiarity with Docker and Kubernetes (nice to have)
• Experience working with APIs, microservices, and scalable AI application architectures (nice to have)
• Strong problem-solving and communication skills
• Ability to work effectively in a fast-paced, collaborative environment

• Advanced training
• Opportunity to apply advanced training to real business solutions
• Remote work arrangement
• Contract role