MLOps Engineer

Reposted 12 Days Ago
Be an Early Applicant
London, Greater London, England, GBR
In-Office
Mid level
Energy • Renewable Energy
The Role
The MLOps Engineer will enhance ML infrastructure, deploying and monitoring models, ensuring scalability and security, while collaborating with cross-functional teams.
Summary Generated by Built In

Ohme is on a mission to accelerate the global transition to clean, affordable energy. We do that by serving as an integrated hardware and software smart-grid platform, focused on the residential EV charging market.

The worlds of energy, transport and artificial intelligence are colliding and Ohme is at the heart of this new era. By using technology and data integrations to connect cars, chargers, people, energy providers and more, Ohme has a powerful platform that puts the consumer at the core.

Ohme has been selling its chargers to consumers since mid 2019 and has had exponential growth since. We are now operating in multiple countries and have partnerships with the likes of VW, Mercedes, Octopus Energy, and other innovative brands.

We are scaling up the business and are building out the team for rapid growth. If you’re interested joining a fast-growing cleantech venture on a data and AI-first journey to speed up the global transition to clean, affordable energy, read on!

Job description

We are looking for an MLOps  Engineer to join our growing Data team.

As an MLOps Engineer, you will play a critical role in our optimize our machine learning (ML) infrastructure, ensuring seamless deployment, monitoring, and scalability of ML models and endpoints. There will be the possibility to lean into our Agentic AI workload as well.


Key Responsibilities

  • Collaborate with data scientists, data engineers, and cross-functional teams to deploy, manage and A/B/X test ML models.
  • Set up and maintain MLflow (or similar) for tracking experiments, managing models, and facilitating reproducibility.
  • Design and implement scalable and reliable ML pipelines for model training, validation, and deployment.
  • Ensure the robustness and security of ML endpoints, including monitoring and alerting for performance and reliability.
  • Optimize the infrastructure for cost-effectiveness, performance, and scalability.
  • Establish standards and best practices for MLOps, including CI/CD for ML models.

About You

  • Proven professional experience with MLOps tools and frameworks, particularly MLflow, within an AI first organisation
  • Experience in setting up and managing ML and AI endpoints, preferably through AWS Sagemaker.
  • Strong programming skills in Python and familiarity with ML libraries (e.g., TensorFlow, PyTorch).
  • Possess Infrastructure as Code (IaC) skills, preferably through AWS CDK.
  • Experience with cloud platforms, preferably AWS.
  • Familiarity with containerization and orchestration tools (e.g., Docker).
  • Excellent problem-solving and analytical skills.
  • Great engineering and coaching mindset.
  • Keen interest and curiosity in the ML/AI landscape.
  • Knowledge of the electric vehicle industry is a plus.

 

Benefits

You’ll get to work in a fast-paced and rapidly growing scale-up with global ambitions that is cutting edge, passionate about sustainability and seeks to make the world a better place.

  • Competitive salary and bonus
  • Hybrid office (Office-based with the option to work 2 days remotely)
  • Beautiful central London office
  • Private Health Insurance
  • Aegon Pension Scheme
  • Life Assurance Scheme with death in service benefit of 4x salary
  • Income Protection Scheme for long term illness
  • Ride to Work Scheme
  • Payroll Giving Scheme
  • Season Ticket Loan to spread cost of travel over 12 months

Diversity, Equity and Inclusion are at the heart of what we do and we encourage a culture where everyone can be themselves at work. We actively seek out a diverse range of talent and our policies ensure that every job application and employee is treated fairly, with equal opportunity to succeed and to feel included.


Skills Required

  • Proven professional experience with MLOps tools and frameworks, particularly MLflow
  • Experience in setting up and managing ML and AI endpoints, preferably through AWS Sagemaker
  • Strong programming skills in Python and familiarity with ML libraries (e.g., TensorFlow, PyTorch)
  • Possess Infrastructure as Code skills, preferably through AWS CDK
  • Experience with cloud platforms, preferably AWS
  • Familiarity with containerization and orchestration tools (e.g., Docker)
  • Excellent problem-solving and analytical skills
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The Company
HQ: London
218 Employees
Year Founded: 2017

What We Do

Hello, we’re Ohme 👋 We provide end-to-end electric charging solutions for customers and businesses. Whether you are charging at home, at work or on the move - we have you covered. We’ve created a product that not only makes electric vehicles cheaper to run, but allows consumers, businesses and energy suppliers to work together to support the global transition to renewables. Want to find out more? Head to www.ohme-ev.com or email [email protected]. #ohmeev

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