Lead AI/ML Engineer

Job Title: Lead Software Engineer – Machine Learning & AI
Location: India (Remote/Hybrid) — Must be willing to work onsite in Dubai if required

NorthBay Solutions is seeking a highly experienced Lead Software Engineer with deep expertise in Machine Learning (ML) and Artificial Intelligence (AI). The ideal candidate will have a strong background in NLP, LLMs, Computer Vision, and cloud-based ML services. This is a high-impact leadership role requiring hands-on technical skills, strategic thinking, and the ability to mentor and manage engineering teams.

• 12+ years of overall experience in software development, with at least 8 years focused on ML/AI.
• Proven experience in delivering 5 or more successful AI/ML projects involving:
  • Model fine-tuning
  • Foundational model training
  • Vector embeddings
  • Product integration
  • Human-in-the-loop systems
  • Multimodal architectures
• Strong hands-on expertise with:
  • LLMs (e.g., GPT), Prompt Engineering, Chatbots, Vector Databases, LangChain
  • NLP, Text Classification, Computer Vision, Object/Event Detection, Inference Pipelines
• Proficient in Python, Jupyter Notebooks, and ML libraries such as NumPy, pandas, PySpark, TensorFlow, OpenCV, YOLO
• Experience with AWS ML Services: SageMaker, Ground Truth, ECS, Cognito, Lambda, CloudWatch, API Gateway, PostgreSQL (RDS)
• Ability to lead teams and mentor engineers in an Agile development environment
• Strong communication and stakeholder management skills
• AWS certification is a plus
• Willingness to travel and work onsite in Dubai if required

• Lead the architecture, design, and development of scalable AI/ML models and end-to-end pipelines.
• Drive innovation in NLP, LLMs, and computer vision solutions, aligning with business goals.
• Collaborate with product and engineering teams to integrate ML models into enterprise systems.
• Provide hands-on expertise in tuning, deploying, and monitoring models in production environments.
• Evaluate and implement appropriate frameworks and AWS tools for various ML/AI use cases.
• Manage, mentor, and grow a team of ML engineers and data scientists.
• Ensure model performance, code quality, and system reliability through continuous validation and optimization.
• Act as an internal consultant and thought leader in the ML/AI domain.