Lead ML Engineer
Sign up free to see how well your resume matches this role.
What you'll do
- Establish standard, reusable patterns for model serving, pipelines, and deployment.
- Define standards for model packaging, versioning, CI/CD, monitoring and observability.
- Set clear production readiness criteria for models entering engineering workflows.
- Provide technical direction for ML solutions delivered within the team.
- Evolve platform capabilities that reduce bespoke approaches over time.
- Reduce engineering effort required to productionise models by establishing reusable approaches and platform capabilities.
What they're looking for
- Experience building and operating ML systems in production, including model serving, monitoring, and lifecycle management.
- Strong understanding of serving patterns across batch and real ‑ time environments, and how models move from training to production.
- Experience defining engineering approaches that enable Data Science teams to deliver reliable, production ‑ ready models.
- Ability to turn ambiguity into clear, adoptable technical standards and reusable patterns.
- Experience setting technical direction and influencing engineering practices across teams.
- Hands ‑ on experience with cloud ML platforms (e.g., AWS SageMaker) and orchestration tools (e.g., Airflow, Step Functions)
- Strong communication skills and the ability to collaborate across Data Science, Engineering, and Data Platforms.
Summarised by NextRaise from the employer’s description, which follows in full below.
Full description from employer
Are you ready to define how machine‑learning systems are delivered, operated, and scaled across a data‑driven organisation? NewDay are looking for a Lead ML Engineer to set the standards, patterns, and technical foundations that define how machine learning models are delivered and operated in production.
Why this role matters
As the technical lead within our MLOps function, you will shape how ML is engineered in practice. This role will focus on establishing the standards, patterns, and technical approaches that enable models to move reliably from experimentation into robust production.
You will shape how ML systems are engineered in practice through clear lifecycle standards, reusable approaches, and strong technical foundations.
How you'll contribute
Establish standard, reusable patterns for model serving, pipelines, and deployment.
Define standards for model packaging, versioning, CI/CD, monitoring and observability.
Set clear production readiness criteria for models entering engineering workflows.
Provide technical direction for ML solutions delivered within the team.
Evolve platform capabilities that reduce bespoke approaches over time.
Reduce engineering effort required to productionise models by establishing reusable approaches and platform capabilities.
We’re looking for these essential skills
Experience building and operating ML systems in production, including model serving, monitoring, and lifecycle management.
Strong understanding of serving patterns across batch and real‑time environments, and how models move from training to production.
Experience defining engineering approaches that enable Data Science teams to deliver reliable, production‑ready models.
Ability to turn ambiguity into clear, adoptable technical standards and reusable patterns.
Experience setting technical direction and influencing engineering practices across teams.
Hands‑on experience with cloud ML platforms (e.g., AWS SageMaker) and orchestration tools (e.g., Airflow, Step Functions)
Strong communication skills and the ability to collaborate across Data Science, Engineering, and Data Platforms.
How you work
You are comfortable operating at the boundary between experimentation and production‑grade ML delivery.
You value structure, consistency, and high standards in engineering practices.
You think in terms of reusable frameworks rather than one‑off solutions.
You are motivated by improving reliability and long‑term maintainability of ML systems.
You bring clarity, direction, and technical leadership to complex problem spaces.
#LI-Hybrid
#LI-TM1
At NewDay, we value all types of diversity. We’re an equal opportunity employer and believe that our differences create a vibrant, authentic working culture. We want all our colleagues to feel able to bring their whole selves to work. We don’t discriminate on the basis of protected characteristics or identities. We make sure that every job is crafted to be inclusive and that people with disabilities or caring responsibilities can take part in the application and interview process.
Tell us if you need accommodations: We’ll put reasonable adjustments in place to support you.
We work with Textio to make our job design and hiring inclusive.
PermanentCompany
Company facts come from this company's own listings. We only show what the postings themselves carry.