Senior ML Engineer

Role Overview: You are a Senior Machine Learning Engineer responsible for designing, developing, and deploying Computer Vision solutions in production environments. Your role involves leading the design, development, and deployment of advanced computer vision systems that automate AI across various operational workflows. You will be accountable for the entire solution lifecycle, from problem scoping to deployment and monitoring, working alongside a team of ML engineers. Key Responsibilities: - Lead the design and deployment of computer vision models for applications such as object detection, tracking, human activity analysis, and visual quality control. - Build and optimize image and video data pipelines to ensure robust data flow from sensors, cameras, and other sources. - Architect real-time vision systems that prioritize latency, accuracy, and scalability for edge and cloud environments. - Mentor and guide junior ML engineers, promoting a high technical standard and collaborative problem-solving culture. - Stay updated on cutting-edge computer vision research, evaluating and integrating new models (e.g., ViTs, SAM, Grounding DINO) into existing workflows. - Engage directly with clients and internal stakeholders on AI solutioning, PoCs, and consulting projects. Qualifications: - Minimum of 3 years of experience in Machine Learning within Computer Vision projects deployed in production, including optimizing models for runtime. - Proficiency in Python and proven expertise in computer vision applications like object detection, facial recognition, defect detection, and tracking using libraries such as PyTorch, TensorFlow, OpenCV, etc. - Solid understanding of MLOps workflows, data pipelines, and scalable deployment strategies. - Previous experience in leading ML teams, mentoring engineers, and managing project deliverables. - Comfortable working in an agile, startup-like environment that values problem-solving and ownership. - Excellent communication skills to translate complex technical concepts into actionable project plans. Good to Have: - Experience with vision-based automation in the manufacturing industry. - Exposure to Generative AI workflows. - Experience with Large Language Models (LLMs) and building multi-modal AI pipelines. - Understanding of AI governance, data compliance, and security protocols. Please note that additional details about the company were not provided in the job description.,