Overview

About Biz-Tech Analytics

Responsibilities

• Lead the design, development, deployment, and optimisation of Computer Vision and Machine Learning solutions for real-world production applications.
• Oversee solutions involving object detection, object tracking, human activity analysis, visual quality control, image/video analysis, facial recognition, and automated inspection systems.
• Work closely with ML engineers and technical teams to define technical approaches, architecture, models, datasets, evaluation methods, and deployment strategies.
• Review technical solutions and ensure that models meet requirements for accuracy, latency, scalability, reliability, and production performance.
• Evaluate and introduce relevant Computer Vision and AI technologies, including Vision Transformers (ViTs), SAM, Grounding DINO, multimodal models, and Generative AI workflows.
• Guide the development of image and video data pipelines across camera, sensor, edge, and cloud environments.
• Ensure effective MLOps practices, including model deployment, monitoring, versioning, experimentation, and performance optimisation.
• Own the end-to-end planning and execution of AI/ML projects, from initial problem definition and requirements gathering through development, deployment, and post-deployment monitoring.
• Translate business and client requirements into clear technical requirements, project scopes, milestones, deliverables, and execution plans.
• Work closely with engineering, data, product, and business teams to ensure projects remain aligned with objectives, timelines, and quality standards.
• Define project priorities, dependencies, resources, timelines, and deliverables.
• Track project progress, identify risks and blockers, and drive timely resolution with the relevant teams.
• Manage multiple AI/ML projects and priorities simultaneously while ensuring effective resource allocation.
• Participate in PoCs, product development, solution design, and client consulting engagements.
• Help identify opportunities to convert AI/ML capabilities into scalable products and repeatable solutions.
• Collaborate with stakeholders to define product requirements, success metrics, acceptance criteria, and expected business outcomes.
• Lead and manage a team of ML Engineers, Computer Vision Engineers, and other technical contributors.
• Mentor engineers and provide technical and project-level guidance throughout the development lifecycle.
• Assign responsibilities based on team capabilities, project requirements, and timelines.
• Conduct regular project and team reviews to track progress, quality, and performance.
• Establish high technical and execution standards across the team.
• Identify skill gaps and support team members through mentoring, knowledge sharing, and structured development.
• Act as the bridge between technical teams, product/business stakeholders, and clients.
• Work directly with clients and internal stakeholders to understand business problems and translate them into practical AI/ML solutions.
• Lead technical discussions, requirement-gathering sessions, solution presentations, and project updates.
• Communicate complex AI/ML concepts clearly to both technical and non-technical stakeholders.
• Manage expectations around project scope, timelines, technical feasibility, and deliverables.
• Present project progress, risks, outcomes, and recommendations to senior stakeholders.
• Build strong working relationships with clients and internal teams throughout the project lifecycle.

Qualifications

• 3+ years of experience working in Machine Learning, Computer Vision, AI Engineering, Technical Product Management, or AI/ML Project Management, with meaningful experience in production environments.
• Strong understanding of Computer Vision and Machine Learning, including experience with areas such as object detection, tracking, image/video analysis, defect detection, facial recognition, or visual inspection.
• Strong proficiency in Python and familiarity with frameworks and libraries such as PyTorch, TensorFlow, OpenCV, or equivalent.
• Proven experience managing AI/ML projects or products from problem definition through development and production deployment.
• Demonstrated experience in leading technical teams, mentoring engineers, allocating work, and managing project deliverables.
• Strong understanding of MLOps, data pipelines, model deployment, cloud/edge infrastructure, and production ML systems.
• Strong project management skills, including planning, prioritisation, resource management, risk management, timelines, and delivery tracking.
• Ability to understand technical architecture and make informed decisions without necessarily being the primary hands-on developer for every component.
• Excellent communication and stakeholder-management skills.
• Comfortable working in a fast-paced, startup-like environment that requires ownership, adaptability, and independent problem-solving.
• Understanding of AI governance, data privacy, compliance, security, and responsible AI practices.
• Familiarity with Agile/Scrum methodologies and project management tools.