Machine Learning Operations Manager

Machine Learning Operations Manager

Our client is an automotive supplier and partner to automakers worldwide. As a technology company, they design innovative solutions for smart mobility, with a particular focus on safer driving and reducing CO2 emissions.

Their mission is to deliver market-leading perception solutions for ADAS driving and parking functions. Through their state-of-the-art, data-driven approach, they harness the expertise of the company's global community to provide safe, reliable, and innovative perception solutions.

They aim to develop and deliver a modular, scalable, and hardware-agnostic full perception stack, utilising the company's technology leadership in sensing and ADAS computing platforms.

Requirements

➔ Lead the ML Ops team globally

➔ Develop end-to-end (Data/Dev/ML) Ops pipelines based on in-depth understanding

of cloud/on-premise platforms, AI lifecycle, and business requirements

➔ Take AI out of the lab and into everyday life on the road for multi-sensor ADAS and

Autonomous Driving perception applications

Your Responsibilities

➔ Co-ordinate a dedicated global team of software engineers to develop and manage

MLOps tools that help automate and improve our deep learning software

development and model building practices

➔ MLOps Strategy: Develop and implement MLOps strategies, roadmaps, best

practices, and standards to enhance AI ML model deployment and monitoring

➔ Infrastructure Management: Oversee the design, deployment, and management of

scalable and reliable infrastructure for model training and deployment, both

on-premise and on the cloud

➔ Monitoring and Optimization: Create and maintain robust monitoring systems to track

model performance, data quality, and infrastructure health

➔ Automation: Develop and maintain automated pipelines for model training, testing,

and deployment, optimizing for speed and reliability. Ensure CI-CD best practices

➔ Internal Collaboration: Collaborate closely with data scientists, ML engineers, and

SW engineers to support smooth integration of ML models into production systems

➔ Stakeholder Engagement and Collaboration: Collaborate closely with business and

PM stakeholders in roadmap planning and implementation efforts and ensure

technical milestones align with business requirements

Education/Training

➔ Degree in Software Engineering or equivalent

➔ Minimum of 3 years relevant experience in AI / MLOps engineering

➔ Strong knowledge of Machine Learning concepts, algorithms, and tools

➔ Experience with data preparation and management tools

➔ Expertise with cloud computing platforms such as AWS, GCP, or Azure

➔ Excellent analysis & trouble-shooting skills using a structured documented approach

➔ Excellent communication skills, both written and verbal

➔ Strong experience in capitalising knowledge & best practices through creation and/or

updating of standards

➔ Strong experience in managing, training and mentoring team members

➔ Confident, articulate, self-motivated, determined & energetic

➔ Self-starter, motivated individual who can work fully autonomously