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 Managing Consultant- Supply Chain Procurement

Company: IBM

Location: Multiple Cities

Posted Dec 18, 2025

This job posting highlights opportunities to work with global industry leaders, drive transformative supply chain projects, and access career growth in an innovation-driven environment. IBM Consulting seeks a Senior Managing Consultant with expertise in supply chain transformation, AI, and global collaboration, emphasizing impactful client engagement and strategic leadership.

Procurement Professional

Company: IBM

Location: BANGALORE, IN

Posted Dec 18, 2025

This text describes a role in IBM Finance & Operations emphasizing collaboration, innovation, and career growth. It highlights responsibilities in procurement processes, compliance, and cross-functional teamwork while promoting IBM's culture of continuous learning and global impact.

Production Engineer

Company: IBM

Location: Mulhuddart, IE

Posted Dec 18, 2025

IBM Software seeks a Platform Production Engineer to scale and optimize multicloud infrastructure. Responsibilities include ensuring platform reliability, automating operations, and collaborating with teams to enhance stability and security. The role emphasizes innovation, growth opportunities, and impactful contributions to digital transformation.

Procurement Professional

Company: IBM

Location: BANGALORE, IN

Posted Dec 18, 2025

This job description highlights IBM's Finance & Operations role, emphasizing career growth, skill development, and collaborative innovation in a dynamic global environment. The position requires procurement expertise in SAP and supply chain concepts, with opportunities for advancement and impactful contributions.

Sr Managing Consultant Supply Chain - Planning & Logistics

Company: IBM

Location: Multiple Cities

Posted Dec 18, 2025

This job posting highlights opportunities to work with global leaders, drive transformative supply chain projects, and access career growth in an innovative environment. IBM Consulting seeks a Senior Managing Consultant with expertise in supply chain transformation, AI, and logistics systems to lead strategic initiatives and collaborate on large-scale programs.

Software Developer Internship 2026

Company: IBM

Location: Austin, US

Posted Dec 18, 2025

IBM's summer internship offers hands-on experience with emerging technologies, collaboration with professionals, and opportunities to develop skills in a global tech environment. The role emphasizes innovation, problem-solving, and contributing to impactful projects while gaining mentorship and industry exposure.

Talent Acquisition – Selection Specialist (Fixed Term)-PH

Company: IBM

Location: Multiple Cities

Posted Dec 18, 2025

This job description for a Recruiting Selection Specialist at IBM highlights opportunities to lead in technology, solve complex problems, and collaborate with stakeholders. The role emphasizes continuous learning, innovative approaches, and contributing to global hiring initiatives while maintaining data integrity and system integrations.

Application Developer-SAP UX

Company: IBM

Location: BANGALORE, IN

Posted Dec 18, 2025

The text promotes IBM Consulting's career opportunities, emphasizing collaboration, innovation, and growth. It highlights roles in hybrid cloud and AI development, long-term client relationships, and professional development. Required skills include SAP UX, BTP services, and programming expertise, with a focus on delivering impactful solutions.

DELIVERY MANAGER-TALENT DEVELOPMENT OPTIMIZATION PROCESSES

Company: IBM

Location: BANGALORE, IN

Posted Dec 18, 2025

This job description highlights a career in IBM Consulting focused on digital transformation, hybrid cloud, and AI initiatives. The role involves managing employee benefits, compensation processes, and ensuring compliance with policies. It emphasizes collaboration, career growth, and working with global clients through strategic partnerships and technology platforms.

Product Manager

Company: IBM

Location: BANGALORE, IN

Posted Dec 18, 2025

This text describes a Senior Product Manager AI role at IBM Software, focusing on driving AI-driven capabilities for enterprise solutions. It highlights innovation, global collaboration, and impactful work in shaping AI integration platforms with strong emphasis on governance and scalability.

Java Fullstack Developer

Company: IBM

Location: BANGALORE, IN

Posted Dec 18, 2025

IBM promotes its AI and data platform capabilities while seeking a Java Fullstack Developer with 7-10 years experience. The role involves AI integration, MCP server design, API architecture, and containerization. Requirements include Java proficiency, Reactjs expertise, RESTful API design, and MCP knowledge.

Pentration Tester

Company: IBM

Location: Pune, IN

Posted Dec 18, 2025

The role involves planning and executing penetration tests on systems and applications, requiring expertise in cybersecurity tools and OWASP vulnerabilities. IBM seeks candidates with a bachelor's degree and experience in manual and automated testing methods.

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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