Machine Learning Jobs

Positions 425,970 Updated daily

Machine learning is reshaping industries from finance to healthcare. Demand for talent spikes as companies adopt predictive analytics, automated underwriting, and personalized medicine. Data‑driven product teams need engineers who can translate theory into scalable solutions using TensorFlow, PyTorch, or AWS SageMaker.

Within the field you’ll find roles such as ML Engineer, responsible for productionizing models, Data Scientist building prototypes, Research Scientist pushing algorithmic frontiers, ML Ops Engineer focusing on CI/CD pipelines, and AI Product Manager bridging tech and business. Typical duties include feature engineering, model training, hyper‑parameter tuning, model monitoring, and collaborating with data engineers to maintain data pipelines.

Salary transparency is vital for ML professionals because the field’s rapid evolution creates pay disparities across domains. Knowing the market range for a TensorFlow‑based model deployer in New York versus a research scientist in Seattle helps candidates negotiate realistic offers, assess equity and bonus structures, and prevent skill‑based wage gaps.

Sr. Sales Manager - Kraken Institutional

Company: Kraken

Location: Hong Kong,Taiwan, Province of China

Posted Dec 20, 2025

Kraken promotes its mission-driven approach to crypto adoption, highlighting a global team, industry leadership, and opportunities for experienced professionals to shape the future of cryptocurrency through innovative products and institutional sales roles.

Data Scientist

Company: KoBold Metals

Location: USA

Posted Dec 20, 2025

KoBold leverages AI and advanced sensors for mineral exploration, achieving significant discoveries with less capital. They're hiring a Data Scientist to enhance their exploration tools and drive innovation in critical metal discovery.

Senior Fullstack Engineer I (Golang & React|Typescript)

Company: TrueML

Location: Argentina,Mexico

Posted Dec 20, 2025

TrueML, a mission-driven financial tech company, uses machine learning to enhance customer experiences for distressed borrowers. They seek a Senior Engineer to develop payments infrastructure, collaborate with UX teams, and contribute to innovative solutions. The role offers competitive compensation and a dynamic, inclusive work environment.

Senior Software Engineer - Data Engineering

Company: Airbnb

Location: USA

Posted Dec 20, 2025

This text describes Airbnb's job opportunities for Senior Data Engineers, highlighting roles in developing data strategies, building tools, and collaborating with cross-functional teams to enhance the Airbnb experience. It emphasizes the impact of the work on product quality and growth, with remote eligibility and inclusion commitments.

Product Manager - Developer Tools

Company: Figma

Location: USA

Posted Dec 20, 2025

Figma seeks a Product Manager with 5+ years of experience to lead dev tools initiatives, emphasizing collaboration, problem-solving, and innovation. The role offers a competitive salary range, equity, and comprehensive benefits, with opportunities to impact user experiences through emerging technologies.

Intermediate Backend Engineer (Ruby on Rails), Plan: Knowledge

Company: GitLab

Location: APAC,EMEA

Posted Dec 20, 2025

This role involves developing backend services and APIs for GitLab's knowledge management tools, focusing on scalability and collaboration with cross-functional teams. The position emphasizes creating robust systems, improving performance, and fostering a collaborative environment for both technical and non-technical users.

Staff Product Designer - Cloud Infrastructure

Company: Netflix

Location: USA

Posted Dec 20, 2025

This job posting highlights Netflix's opportunity to shape cloud infrastructure experiences, emphasizing innovation, technical challenges, and collaboration with cross-functional teams. The role offers impactful work on complex systems and aligns with Netflix's mission to entertain the world through cutting-edge engineering solutions.

Graduate Software Engineer - Open Source and Linux, Canonical Ubuntu

Company: Canonical

Location: Anywhere

Posted Dec 20, 2025

Canonical promotes itself as a leading open-source provider offering global remote engineering roles with challenging projects, competitive opportunities, and a collaborative culture. The job description highlights innovation, professional growth, and a strong emphasis on open-source contributions while outlining requirements and benefits for candidates.

Staff Backend Engineer - PHP + Go

Company: Hostaway

Location: Europe

Posted Dec 20, 2025

Hostaway offers a remote backend engineer role in Europe with competitive pay, equity, and a dynamic team culture. The position involves integrating with partners and solving scalability issues, requiring expertise in PHP/Go and cloud technologies.

Technical Leader of Natural Language Processing

Company: Kitware

Location: USA

Posted Dec 20, 2025

Kitware is a research and development software provider focused on advancing science and making a positive impact through collaborative innovation. They offer opportunities to work on national security projects, collaborate with top institutions, and enjoy competitive benefits. The company emphasizes employee ownership, flexibility, and a supportive work environment.

Senior Data Scientist - Ads

Company: Reddit

Location: USA

Posted Dec 20, 2025

Reddit seeks a Senior Data Scientist to enhance their advertising platform through advanced data science and machine learning. The role offers remote work flexibility, competitive compensation, and benefits like healthcare, equity, and professional development opportunities. The team focuses on improving advertiser value and platform measurement while fostering innovation in ad technology.

Machine Learning Engineer (L5) - Ads

Company: Netflix

Location: USA

Posted Dec 20, 2025

The text provides information about Netflix's global services, membership statistics, and a new ad-supported tier. It outlines the Creative team's mission to develop AI-generated ads, details job responsibilities and requirements, and describes compensation and benefits packages. The content is factual and neutral in tone.

Frequently Asked Questions

What are typical salary ranges by seniority for machine learning roles?
Entry‑level ML Engineer: $90k–$120k; Mid‑level ML Engineer or Data Scientist: $120k–$160k; Senior ML Engineer or Research Scientist: $160k–$220k; Lead ML Engineer or Principal Research Scientist: $200k–$280k; AI Product Manager: $130k–$180k depending on experience and market.
What skills and certifications are most valuable in machine learning today?
Core language: Python; Deep learning frameworks: TensorFlow, PyTorch; Scikit‑learn for classical models; SQL and NoSQL databases for data ingestion; Docker and Kubernetes for deployment; Cloud AI services such as AWS SageMaker, GCP Vertex AI, Azure ML. Certifications: TensorFlow Developer Certificate, AWS Certified Machine Learning – Specialty, GCP Professional Machine Learning Engineer.
How common is remote work for machine learning positions?
Over 70% of ML roles allow full remote or hybrid arrangements. Startups and fintech firms tend to offer 100% remote options, while larger enterprises often provide hybrid models with occasional on‑site data‑center visits. Remote work is especially prevalent for roles focused on model training and research.
What career progression paths exist in machine learning?
Typical paths: ML Engineer → Senior ML Engineer → Lead ML Engineer → ML Manager; Data Scientist → Senior Data Scientist → Lead Data Scientist → Head of Data; Research Scientist → Senior Research Scientist → Principal Scientist → Chief Data Scientist; ML Ops Engineer → Senior ML Ops Engineer → Lead ML Ops Engineer → Director of MLOps. Progression often involves moving from coding to architecture, then to leadership and strategy.
What are the current industry trends shaping machine learning hiring?
Key trends: reinforcement learning for autonomous systems; federated learning for privacy‑preserving models; edge AI for IoT devices; AutoML platforms speeding model deployment; MLOps practices for scalable pipelines; explainable AI and ethics compliance; and increased demand for AI governance roles.

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