Senior ML Engineer

Lime; Remote; CAD 100,000 - 130,000; Full time

Job summary

A global tech company is seeking a Senior Machine Learning Engineer to build and scale ML systems that optimize vehicle positioning and demand forecasting. You will collaborate with multidisciplinary teams and drive the application of state-of-the-art technologies in production systems. The ideal candidate has 5+ years of experience, strong Python skills, and a passion for mentoring. This role offers innovative perks including health benefits, financial planning, and flexibility, making Lime an ideal workplace for impactful careers.

Benefits

Comprehensive Health & Wellness

Financial & Retirement Planning

Family & Fertility Support

Flexible vacation policy

Complimentary use of Lime vehicles

Qualifications

• 5+ years of professional software engineering and ML experience.
• Strong coding skills in Python and experience with modern ML frameworks.
• Experience with data exploration and insights driving business impact.
• Skilled in taking ML models from prototype to production.
• Strong collaborator in cross-functional environments.

Responsibilities

• Build and improve demand forecasting and vehicle positioning algorithms.
• Drive execution of Lime’s multi-year ML strategy.
• Collaborate with product managers and engineers.
• Mentor and coach engineers.

Skills

Python

Modern ML frameworks

Data tools (SQL, Spark, Pandas)

Demand forecasting

Cross-functional collaboration

Job description

Lime is the largest global shared micromobility business, operating in close to 30 countries across five continents. We’re on a mission to build a future where transportation is shared, affordable and carbon-free. Our electric bikes and scooters have powered more than one billion rides in cities around the world. Named a 2025 Time 100 Most Influential Company, Lime continues to set the pace for shared micromobility globally, spurring a new generation of clean alternatives to car ownership.

At Lime, our mission is to ensure a scooter or bike is ready for you at the right place and the right time. Achieving this requires solving one of the most complex optimization problems in mobility: how to deploy and continually rebalance vehicles across a dynamic, ever-changing city. The Machine Learning team is central to this mission, building demand forecasts, recommending deployment strategies, and creating models that directly influence millions of rides worldwide.

As a Senior Machine Learning Engineer, you will design, build, and scale ML systems that power these decisions. You’ll partner with data scientists, operators who know their cities block-by-block, and engineers across the stack to deliver solutions that bridge cutting‑edge algorithms with real‑world execution.

What You’ll Do:

• Build and improve Lime’s demand forecasting and vehicle positioning algorithms to ensure riders have access to a scooter or bike when and where they need it.

• Drive execution of Lime’s multi‑year ML strategy, applying state‑of‑the‑art technologies, processes, and techniques to production systems at global scale.

• Collaborate with product managers, data scientists, engineers, and operations leaders to make high‑impact technical and product decisions.

• Mentor and coach engineers, raising the bar on ML expertise and engineering excellence across the team.

About You:

• 5+ years of professional software engineering and ML experience, with a track record of building and scaling successful products.

• Strong coding skills in Python and experience with modern ML frameworks (e.g., PyTorch, TensorFlow) and data tools (SQL, Spark, Pandas).

• Skilled at turning data exploration and insights into business‑impacting projects, including applying machine learning to drive measurable value.

• Experienced in taking ML models from prototype to production, including deployment, monitoring, and iteration.

• Strong collaborator who thrives in cross‑functional environments, partnering with product, operations, and engineering teams to translate business needs into technical solutions.

• Passionate about mentoring and raising the technical bar, helping teammates grow and shaping team culture.

Preferred Experience:

• Expertise in time‑series modeling and demand forecasting at scale.

• Background in optimization or operations research, particularly applied to logistics, scheduling, or large‑scale planning problems.

• Familiarity with A/B testing, causal inference, or other experimentation methods to evaluate ML‑driven impact.

• Experience with geospatial or spatiotemporal data in applied ML.

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What We Offer

• Comprehensive Health & Wellness: A choice of medical, dental, and vision plans, with Lime covering 100% of the employee‑only premium for many plans. We also provide company‑paid life and disability insurance and company‑funded mental health benefits.

• Financial & Retirement Planning: 401(k) plan with both pre‑tax and Roth options, and access to a Health Savings Account (HSA) with a monthly company contribution.

• Family & Fertility Support: Paid parental leave for birthing and non‑birthing parents, plus fertility and family‑forming benefits.

• Time Off & Flexibility: Flexible vacation policy for exempt employees, paid sick time, and a calendar of paid company holidays.

• Unique Lime Perks: Complimentary use of Lime vehicles in participating cities, a monthly phone allowance, dedicated learning and development days, and access to perks including One Medical, Wellhub, and Headspace.

Note: Benefits and perks vary depending on role, location, and plan eligibility.

If you want to make an impact, Lime is the place for you. Not sure if you meet all the qualifications? If this role excites you we encourage you to apply. Explore all opportunities on our career page.

Lime is proud to be an Equal Opportunity Employer. We believe different perspectives help us grow and achieve more. That’s why we’re dedicated to building and developing a team that reflects a wider range of backgrounds, abilities, identities, and experiences. If you require a reasonable accommodation during the application or hiring process, please email [e-mail] for assistance.