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Senior Machine Learning Engineer (Remote)

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Role: Senior Machine Learning Engineer
Location: Remote
Employment Type: Full-time
Compensation: Competitive salary commensurate with experience, qualifications, and location. Indicative range: $150,000 – $250,000 (USD equivalent), plus benefits.
Role Overview
We are hiring a Senior Machine Learning Engineer to lead the design, training, and deployment of ML systems in production. The role combines deep ML expertise with strong software engineering — owning models from research through scaled inference.
Key Responsibilities
- Design, train, and deploy machine learning models at production scale
- Lead architecture decisions for training, evaluation, and inference pipelines
- Build evaluation frameworks and monitoring for model quality and drift
- Partner with data engineering on training data pipelines and feature stores
- Mentor junior ML engineers and contribute to ML practice
- Stay current on research and bring proven techniques into production
Reasons to use Rodeo
I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?
Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.
Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.
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Grad scheme, placement, apprenticeship? Not sure what you want yet — that's fine. Your agent talks it through with you and turns "I have no idea" into a shortlist.
Graduate Consultant — 2026 Scheme
Why you're a good match
StrongYour economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.
See breakdownIt searches the market for you
Every day your agent scans the market matching roles against what actually matters to you, not just keywords on a CV.
Why you're a good match
You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.
Experience fit
Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.
Only hits
No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
Required Skills and Qualifications
- 5+ years in machine learning engineering with production ownership
- Strong Python skills and deep experience with PyTorch or TensorFlow
- Experience training and serving models at scale (deep learning, LLMs, or classical ML)
- Hands-on with cloud ML infrastructure (AWS Sagemaker, GCP Vertex, Databricks, or similar)
- Strong software engineering fundamentals (testing, code review, system design)
- Track record of shipping ML systems that delivered measurable business value
What You'll Bring
- Curiosity about how models behave and why they fail
- Rigor in following guidelines and flagging ambiguity early
- Strong written communication, including ability to document findings clearly
- Comfort working asynchronously across time zones


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What We Offer
- Fully remote, flexible work hours
- Performance-based bonus structure
- Annual learning & development stipend
- Health and wellness benefits (varies by location)
- Opportunity to work on high-scale, real-world impact projects
Equal Opportunity Statement
This is an equal opportunity role. Applications are welcomed from all qualified individuals regardless of race, color, ethnicity, nationality, gender, gender identity or expression, sexual orientation, age, religion, disability, marital status, or any other characteristic protected by applicable law. All hiring decisions are based solely on qualifications, skills, and demonstrated ability.
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