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Lead AI ML Engineer

5-8 years

AI/MLAI/ML
Sri LankaSri Lanka
Full-TimeFull-Time
HybridHybrid
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Who We’re Looking For: 

As a Lead AI/ML Engineer, you will give technical leadership to the team in the architecture, design, and end-to-end delivery of scalable AI and Machine Learning models into production designing, building, and deploying intelligent systems, algorithms, and models that learn from data and solve complex problems. 

 

Key Responsibilities: 

  • Infrastructure & MLOps: Set up CI/CD pipelines, containerization, and orchestration (e.g., Docker, Kubernetes, Terraform) to ensure smooth deployments.  

  • Model Evaluation & Monitoring: Implement automated frameworks for tracking model drift, performance validation, and version control. 

  • Team Mentorship: Provide technical mentorship to junior engineers and Data Scientists, enforcing coding and AI development best practices.  

  • Stakeholder Alignment: Translate business goals into technical architectures, partnering with product and engineering teams. 

 

Technical Skills & Experience: 

  • Experience: 5 to 8 years in software/data engineering, with 3+ years specifically in ML and Generative AI. 

  • Tech Stack: Expert-level Python programming; experience with frameworks like LangChain or LlamaIndex; and knowledge of API development (FastAPI). 

  • Data & Cloud: Experience with cloud platforms (AWS, Azure, GCP) and vector databases (Pinecone, Qdrant). 

  • Proven ability to communicate technical concepts to non-technical stakeholders and resolve complex architectural problems.  

  • Guide and mentor senior and junior engineers on the team 

  • Extensive experience in classification, time series analysis, pattern recognition, reinforcement learning, deep learning, dynamic programming, and optimization techniques. 

  • Ability to identify high-impact data analytics problems and determine the most relevant datasets and variables. 

  • Experience in collecting, cleaning, validating, and processing large structured and unstructured datasets from diverse sources. 

  • Proficiency in developing and applying models and algorithms to extract insights from big data. 

  • Strong analytical skills to identify trends and patterns in data and derive actionable insights.