Machine Learning Engineer Computer Vision

About Biz-Tech Analytics

At Biz-Tech Analytics, we build production-grade computer vision and AI-driven automation solutions. From visual quality control systems to workforce productivity intelligence, we focus on turning complex data into actionable insights through scalable AI infrastructure.

We are looking for a Senior Machine Learning Engineer who can take ownership of designing, developing, and deploying Computer Vision solutions in production environments.

Responsibilities

As a Senior ML Engineer, you will lead the design, development, and deployment of advanced computer vision systems that power AI automation across diverse operational workflows. You will take ownership of the entire solution lifecycle, from problem scoping, model development, to deployment and performance monitoring, with a team of ML engineers.

• Lead design and deployment of computer vision models for applications like object detection, tracking, human activity analysis, and visual quality control.
• Build and optimise image and video data pipelines, ensuring robust data flow from sensors, cameras, and other sources.
• Architect real-time vision systems, focusing on latency, accuracy, and scalability for edge and cloud environments.
• Mentor and guide junior ML engineers, fostering a culture of high technical standards and collaborative problem-solving.
• Stay updated with cutting-edge computer vision research, evaluating and integrating new models (e.g., ViTs, SAM, Grounding DINO) into existing workflows.
• Work directly with clients and internal stakeholders on AI solutioning, PoCs, and consulting projects.

Qualifications

• At least 2+ years of experience in Machine Learning in Computer Vision projects deployed in production, and optimising models for runtime.
• Proficiency in Python and proven expertise in computer vision applications like object detection, facial recognition, defect detection and tracking using libraries like 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.

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• Comfortable working in an agile, startup-like environment where problem-solving and ownership are key.
• 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.