Machine Learning Engineer Jobs
62 genuine, current openings aggregated from public job boards — Remotive, Jobicy, Arbeitnow and RemoteOK. JobStraight never reposts stale listings: each card links straight to the original posting. Before you apply, paste the job into TrueFit to see your honest fit score, tailor your resume in Resume Studio, and rehearse with AceCoach — all free.
Job Description: Data Scientist with Machine learning Location: Pune, India Experience: 5-8 Years Role Type: Full-Time About the Role We are seeking a highly motivated Data Scienti…
As the Engineering Manager for Data Science, you will lead a high-performing team of Data Scientists, Machine Learning Engineers, and Data Engineers. You will sit at the intersecti…
About Brillio: Brillio is one of the fastest growing digital technology service providers and a partner of choice for many Fortune 1000 companies seeking to turn disruption into a …
Job Description We're looking for a Machine Learning Engineer to join our Search & Recommendations team , where we build the machine learning systems that help millions of customer…
About the team The Agentic AI team at Zillow is at the forefront of transforming the real estate industry by helping millions of people use AI assistants to find their next home.…
Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and syst…
Distinguished Machine Learning Engineer Overview: As a Capital One Machine Learning Engineer, you'll be providing technical leadership to engineering teams dedicated to productioni…
Senior Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications a…
Sr. Distinguished Machine Learning Engineer Overview: As a Capital One Machine Learning Engineer, you'll be providing technical leadership to engineering teams dedicated to product…
This job is with LexisNexis Legal & Professional®, an inclusive employer and a member of myGwork – the largest global platform for the LGBTQ business community. Please do not conta…
£65,000 GBP Onsite WORKING Location: Central London, Greater London - United Kingdom Type: Permanent An opportunity is available for an experienced Senior Machine Learning Engineer…
White Collar Factory (95009), United Kingdom, London, London Staff Software Engineer - Machine Learning About this role We’re on a mission to transform the way we use data and AI t…
POSITION SUMMARY The AI/ML Engineer will participate in building, documenting, and refactoring production-grade AI/ML pipelines, model integration layers, and scalable features tha…
Sr Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and s…
Own model training and post-training pipelines end to end: SFT, RLHF, PPO, DPO, and reward model training in PyTorch Build and maintain the infrastructure around RL training: rollo…
Our mission is to make the world programmable. Sight is one of the key ways we understand the world, and soon this will be true for the software we use, too. We’re building the too…
hackajob is partnering directly with Kingfisher to hire for this role. We're Kingfisher, A team made up of over 74,000 passionate people who bring Kingfisher - and all our other br…
hackajob is partnering directly with LexisNexis to hire for this role. Machine Learning Engineering Lead Are you passionate about designing and deploying intelligent machine learni…
Salary: £48,000 - 88,000 per year Requirements: Good understanding of computer science fundamentals, including data structures, algorithms and software design Practical experience …
Salary: £59,000 - 99,000 per year Requirements: First degree in a relevant STEM subject 3 years of industry experience building production ML systems Expertise in Python and PyTorc…
This job is with S&P Global, an inclusive employer and a member of myGwork – the largest global platform for the LGBTQ business community. Please do not contact the recruiter direc…
Key Responsibilities Design, develop, and fine-tune LLM-based applications. Build and optimize NLP models for tasks such as text classification, entity extraction, sentiment analys…
This job is with eBay, an inclusive employer and a member of myGwork – the largest global platform for the LGBTQ business community. Please do not contact the recruiter directly. A…
This job is with eBay, an inclusive employer and a member of myGwork – the largest global platform for the LGBTQ business community. Please do not contact the recruiter directly. A…
This job is with eBay, an inclusive employer and a member of myGwork – the largest global platform for the LGBTQ business community. Please do not contact the recruiter directly. A…
This job is with eBay, an inclusive employer and a member of myGwork – the largest global platform for the LGBTQ business community. Please do not contact the recruiter directly. A…
At Bazaarvoice, we create smart shopping experiences. Through our expansive global network, product-passionate community & enterprise technology, we connect thousands of brands and…
hackajob is partnering directly with Kingfisher to hire for this role. We're Kingfisher, A team made up of over 74,000 passionate people who bring Kingfisher - and all our other br…
This job is with HP, an inclusive employer and a member of myGwork – the largest global platform for the LGBTQ business community. Please do not contact the recruiter directly. Sen…
Machine Learning Engineer (LLM & Agent Evaluation) Mid to senior ML Engineering role at a fast-scaling, AI-first software business Build scalable evaluation infrastructure and mult…
This job is with S&P Global, an inclusive employer and a member of myGwork – the largest global platform for the LGBTQ business community. Please do not contact the recruiter direc…
This job is with S&P Global, an inclusive employer and a member of myGwork – the largest global platform for the LGBTQ business community. Please do not contact the recruiter direc…
This role is for one of Weekday’s clients Salary range: Rs 500000 - Rs 1000000 (ie INR 5 - 10 LPA) Min Experience: 3 years Location: Bengaluru, Karnataka, India JobType: full-time …
Machine Learning Engineer £700-750/day overall assignment rate to umbrella Fully remote 6 month initial Apply today to join a forward-thinking, tech-driven FTSE 100 organisation us…
Machine Learning Engineer DATA & MACHINE LEARNING | FINANCIAL SERVICES Most machine learning roles focus on building models. This one is about making sure they actually work in pro…
The Opportunity: A leading connected commerce marketing business is seeking a Machine Learning Engineer to join its London-based team on a hybrid basis. The organisation partners w…
Job title: Machine Learning Engineer Locations: Manchester or Haywards Heath (hybrid working) Role overview Markerstudy Group are looking for a Machine Learning Engineer to help ta…
Machine Learning Engineer Location: Bangalore (2 days/office) Experience: 8 Years Employment Type: Contract Role Overview We are looking for an expert-level Machine Learning Engine…
Job Description – Machine Learning Engineer Position Machine Learning Engineer Experience 3–8 Years Job Summary We are looking for an experienced Machine Learning Engineer to desig…
This job is with Morningstar, an inclusive employer and a member of myGwork – the largest global platform for the LGBTQ business community. Please do not contact the recruiter dire…
Machine Learning Engineer £75k-£100k DOE | UK Remote About the Role We are seeking an experienced Machine Learning Engineer to develop, train and optimise advanced computer vision …
Machine Learning Engineer Are you interested in an exciting opportunity to drive success with data? The Data Science & Analytics group at the Goodyear does just that. Since its inc…
Embedded Machine Learning and Real-Time Sensor Classification Introduced by: KO2 Embedded Recruitment Solutions Client Location: Edinburgh Salary: £60,000 to £70,000 per annum The …
This job is with Warner Bros. Discovery, an inclusive employer and a member of myGwork – the largest global platform for the LGBTQ business community. Please do not contact the rec…
This job is with Warner Bros. Discovery, an inclusive employer and a member of myGwork – the largest global platform for the LGBTQ business community. Please do not contact the rec…
This job is with Warner Bros. Discovery, an inclusive employer and a member of myGwork – the largest global platform for the LGBTQ business community. Please do not contact the rec…
This job is with Warner Bros. Discovery, an inclusive employer and a member of myGwork – the largest global platform for the LGBTQ business community. Please do not contact the rec…
Company description Forgis is building the intelligent layer for manufacturing plants, an orchestration platform that integrates machines across vendors, hardware types, and applic…
*This is a self-funded career programme with a guaranteed job on completion or 100% of your course fees back* Train. Certify. Get Hired. AI is expected to generate 170 million jobs…
Machine Learning Engineer About the Company Cartesian is building spatial intelligence for indoor environments to drive operational efficiency. We're tackling one of the biggest ch…
We are actively searching for a talented and experienced Machine Learning ML Engineer to join our team As a Machine Learning Engineer you will play a crucial role in the developmen…
Page 1 of 2 ML Engineering Role, FTE'26 Are you an aspiring Machine Learning Engineer with interest in statistics / economic modelling looking for an opportunity to take on new cha…
Career Category Engineering Job Description Role Description We are seeking an experienced Machine Learning Engineer to design, develop, deploy, and support scalable machine learni…
Senior Machine Learning Engineer – Hardware Acceleration - £80k - £120k – London Hexwired Recruitment is recruiting for a rapidly expanding Electronics manufacturer based in London…
Machine Learning Engineer Most machine learning roles talk about building models. This one is about making sure they actually work in production. You'll join a newly formed ML Engi…
Location: Wokingham - Office based (hybrid working with 3 days per week onsite may be considered) Start Day: ASAP Contract Rate: £460 per day inside IR35 Duration: 6 months initial…
Machine Learning Engineer/ Computer Vision Engineer We are working with an innovative UK technology business developing AI powered software solutions that combine multiple data sou…
Machine Learning Engineer (For client company) Location: Bengaluru, India (Hybrid/Onsite) Experience: 3–4 years The Role We are looking for a Machine Learning Engineer to build and…
We tackle the most complex problems in quantitative finance, by bringing scientific clarity to financial complexity. From our London HQ, we unite world-class researchers and engine…
We tackle the most complex problems in quantitative finance, by bringing scientific clarity to financial complexity. From our London HQ, we unite world-class researchers and engine…
With multiple awards to our name, Larian Studios has proven that we’re dedicated to delivering high-quality role-playing games As we move on to new projects, the studio that brough…
Job Description Sr. Lead Machine Learning Engineer\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n As a Capital One Machine Learning Engineer (MLE) , you'll be part of an Agile t…
Before you apply
Application volume is the defining feature of this market. LinkedIn has been reported to process around 11,000 job applications per minute — roughly a 45% year-on-year rise — and recruiters describe receiving 300–500 applications on a popular role within three days. The practical consequence is that being a plausible candidate is no longer enough; you need to be an obvious one for the specific posting.
Two checks are worth doing before every application. First, the knockouts — work authorisation, years of experience, location and on-site expectations are filterable fields, and failing one ends the application regardless of how strong the rest is. Second, keyword coverage: make sure every skill you genuinely have that the posting names appears in your resume in the posting's own words. That is coverage, not density, and it never means adding skills you don't have. The widely-repeated claim that ATS software auto-rejects 75% of resumes is a myth traceable to a 2012 sales pitch — what actually filters you is those knockout fields plus a recruiter's six-to-eight-second scan, as our ATS guide explains with sources.
What machine learning engineer roles advertise
- ›Indian — middle half ₹9.8L to ₹24L, from 153 postings with a figure
- ›UK — middle half £69k to at least £70k, from 187 postings with a figure
- ›US — middle half $107k to at least $140k, from 2,172 postings with a figure
These come from job postings, most of which state no pay at all, and a share of the figures that exist are the source's estimate rather than a number an employer published — the salary page states that share per country. Read them as the posted market you negotiate against rather than as what the average machine learning engineer is paid. The full distribution, the 12-month trend and who is hiring →
Machine Learning Engineer interview questions you should be ready for
These are questions that recur in machine learning engineer interviews, with the structure of a strong answer. They're from our own question bank — not scraped from review sites.
Explain supervised vs unsupervised learning. Conceptual
- Supervised: labelled examples, learn a mapping from input to label.
- Classification predicts a category; regression predicts a number.
- Unsupervised: no labels — you find structure (clustering, dimensionality reduction).
- Give one real example of each from your own work.
Watch out: Confusing unsupervised learning with reinforcement learning.
At senior level: Add self-supervised approaches and when labelling is too costly.
How do you split data for training and evaluation? Conceptual
- Split train / validation / test, and touch test only once at the end.
- Use k-fold cross-validation when data is limited.
- For time series, split chronologically — never shuffle across time.
- Stratify on the target when classes are imbalanced.
Watch out: Shuffling time-series data, which leaks the future into training.
At senior level: Discuss nested CV and group splits that stop entity leakage.
What is data leakage and how do you prevent it? Conceptual
- Leakage is information in training that won't exist at prediction time.
- Common causes: target-derived features, scaling fitted before the split, future data.
- Fit every transform inside the training fold only — use a pipeline.
- Suspiciously perfect validation scores are the usual symptom.
Watch out: Fitting a scaler or encoder on the full dataset before splitting.
At senior level: Audit feature lineage and enforce point-in-time correctness.
Explain the bias-variance trade-off. Conceptual
- Bias is error from over-simplifying — the model underfits.
- Variance is sensitivity to the training sample — the model overfits.
- Simple models: high bias, low variance. Complex models: the reverse.
- Diagnose from learning curves, then fix with capacity, data or regularisation.
Watch out: Naming the terms without saying how you'd diagnose which you have.
At senior level: Discuss ensembling as variance reduction, boosting as bias reduction.
How would you deploy and monitor a model in production? System design
- Version model, data and code together so results are reproducible.
- Serve behind an API; pick batch vs real-time from the latency requirement.
- Roll out shadow or canary first and compare against the incumbent.
- Monitor input drift and business KPIs, not just uptime.
- Automate retraining triggers and keep one-click rollback.
Watch out: Monitoring server health but never the model's accuracy over time.
At senior level: Discuss feature stores, training/serving skew and a model registry.
What is feature engineering? Give examples. Conceptual
- Turning raw data into signals the model can actually use.
- Examples: windowed aggregations, ratios, date parts, target-safe category encodings.
- Handle missing values deliberately — missingness is often signal.
- Verify every feature is available at inference time.
Watch out: Adding features that don't exist at prediction time.
At senior level: Discuss feature selection and the maintenance cost of each feature.
Predict the full question set for a specific job description →
Before you apply for a machine learning engineer role
- ›Machine Learning Engineer salary dataThe full distribution of advertised pay, with the sample size and date behind every figure.
- ›Machine Learning Engineer resume exampleA full resume for this role, with the bullet structure that survives a recruiter skim.
- ›Machine Learning Engineer interview questionsThe questions this role is actually screened on, and what a strong answer contains.
- ›Score your resume against one of these postingsReal skill overlap and the knockout rules that reject people, not a keyword-density number.
- ›What these postings actually ask forMeasured across 2,411 job descriptions, by role, rather than guessed at.
- ›What every role pays, side by side33 roles across India, the UK and the US, with the sample size and method published.
- ›Every role we track, in one listLive counts per role, with pay and a route in where we have them.
- ›How to become a machine learning engineerThe realistic routes in, what to learn in order, and what gets people rejected.
Listings aggregated from public feeds, last refreshed 2026-09-01. Roles fill quickly, so check the source page before applying — JobStraight is not the hiring employer.
Machine Learning Engineer Jobs — common questions
What salary can a machine learning engineer expect?
In India, roughly 12–18 LPA early and 20–40 LPA at senior level in product companies. The US band is about $130,000–$200,000 mid-level and higher at firms bidding for the same few people; the UK £60,000–£90,000. The premium sits with people who can put a model into production and keep it there.
Do I need a PhD to work in machine learning?
For research roles, usually. For the engineering roles that make up most of the market, no. Those hire on whether you can serve predictions inside a latency budget, watch for drift and retrain on a schedule. The maths you need is enough to defend a model choice, and that is learnable on the job.
Should I learn deep learning or deployment first?
Deployment. Far more teams need someone who can ship and maintain a modest model than need another person who can describe attention. Queues, feature stores, monitoring and A/B testing get you hired sooner, and they turn out to be most of the job once you are in it.