Machine Learning Engineer

• LLM-based Agentic Systems for autonomous workflow execution
• Evaluation, Monitoring, Observability, and MLOps for production-grade AI
• LLM-driven Multilingual Language Understanding and Dialogue Management
• Decision Modeling and Optimization for agent interactions
• ML Systems Design and Infrastructure

Responsibilities

• Design, build, and optimize ML models powering our AI agents and automation systems
• Contribute to the development of scalable ML pipelines and frameworks
• Collaborate with product managers and engineers to deliver ML-powered features
• Implement robust monitoring, evaluation, and retraining workflows for deployed models
• Research and experiment with state-of-the-art LLMs and ML techniques
• Participate in design discussions, model reviews, and performance evaluations

Requirements

• 4+ years of hands-on experience in Machine Learning or Applied AI
• Strong understanding of ML fundamentals (probability, statistics, algorithms)
• Practical experience working with LLMs, NLP, or generative AI systems
• Familiarity with MLOps tools and practices (model deployment, evaluation, monitoring)
• Proficiency in Python and ML libraries (TensorFlow, PyTorch, Hugging Face, etc.)
• Experience with cloud platforms (AWS, GCP, Azure) and containerized environments
• Strong problem-solving and analytical skills
• (Preferred) Contributions to open-source projects, blogs, or Git portfolios demonstrating relevant work.