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Ibm Machine Learning Jobs (NOW HIRING)

IBM

NC · On-site

IBM's culture of internal mobility means you'll have the freedom to explore new technologies ... AI, Machine Learning, Data, Statistical Analysis, Automation tools, Cloud software. * Skills:

Fusemachines

Lead Data Scientist- IBM Watson

New York, NY · On-site

$100K - $150K/yr

Design and implement statistical models, machine learning algorithms, predictive analytics models ... IBM WatsonX: 2+ years of hands-on experience with IBM WatsonX * Agentic AI Tools: Experience with ...

IBM

Associate Data Engineer 2027 - AI & Analytics

Lansing, MI · On-site

$59K - $60K/yr

Foundational understanding of Artificial Intelligence, Machine Learning, Generative AI, or data-driven decision-making concepts gained through coursework, projects, research, certifications, IBM ...

IBM

NY · On-site

$144 - $248/hr

IBM Quantum is building the world's leading quantum computing systems, software, and cloud services ... Exposure to machine learning workflows, including feature engineering, model evaluation, and ...

New

IBM

Senior AI Solution Architect (Boston)

Boston, MA · On-site

A career in IBM Consulting is built on long-term client relationships and close collaboration ... Machine Learning, and enterprise data platforms * Design solutions that are scalable, secure, cost ...

IBM

Senior AI Solution Architect

Boston, GA · On-site

... Azure Machine Learning, and enterprise data platforms • Design solutions that are scalable ... YOUR LIFE @ IBM In a world where technology never stands still, we understand that, dedication to ...

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Ibm Machine Learning information

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$25.5K

$42.6K

$88K

How much do ibm machine learning jobs pay per year?

As of Aug 21, 2026, the average yearly pay for ibm machine learning in the United States is $42,584.00, according to ZipRecruiter salary data. Most workers in this role earn between $32,500.00 and $46,000.00 per year, depending on experience, location, and employer.

What is an IBM Machine Learning engineer?

An IBM Machine Learning Engineer is a professional who designs, builds, and deploys machine learning models using IBM's suite of tools and platforms, such as IBM Watson, SPSS Modeler, and IBM Cloud. They work with large datasets to develop predictive models, automate decision-making processes, and solve complex business problems. These engineers collaborate with data scientists, software developers, and business stakeholders to implement AI solutions that drive innovation and efficiency within organizations.

What are the key skills and qualifications needed to thrive as an IBM Machine Learning engineer?

To excel as an IBM Machine Learning Engineer, you need a solid background in computer science, mathematics, and statistics, typically supported by a relevant degree and experience with machine learning algorithms. Familiarity with IBM tools such as Watson Studio, SPSS Modeler, and cloud-based platforms, along with proficiency in Python or R, is essential. Strong problem-solving, communication, and collaboration skills help you translate business requirements into data-driven solutions. These competencies are crucial for effectively designing, deploying, and maintaining impactful machine learning models within IBM's ecosystem.

What types of projects and collaboration can I expect as an IBM Machine Learning specialist?

As an IBM Machine Learning specialist, you can expect to work on diverse projects ranging from developing predictive models to automating business processes with AI. You will frequently collaborate with data scientists, software engineers, and business analysts to translate complex data into actionable insights. The environment is typically agile and encourages cross-functional teamwork, where you'll participate in regular meetings, code reviews, and brainstorming sessions. These collaborations not only enhance project outcomes but also offer valuable opportunities for professional growth and knowledge sharing.

What is the difference between Ibm Machine Learning vs Data Scientist?

AspectIbm Machine LearningData Scientist
Required CredentialsCertifications in IBM AI/ML tools, programming skillsDegree in CS, statistics, or related field; often certifications in data analysis
Work EnvironmentFocus on developing and deploying ML models using IBM platformsData analysis, model building, and interpretation across various tools
Industry UsagePrimarily in organizations using IBM cloud and AI solutionsAcross industries, using diverse tools and programming languages

IBM Machine Learning specialists focus on deploying ML models within IBM ecosystems, while Data Scientists analyze data and build models using various tools. Both roles require programming skills, but Data Scientists often have broader analytical responsibilities. The choice depends on whether you prefer working within IBM platforms or a more general data analysis environment.

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Ibm Machine Learning jobs near you
Infographic showing various Ibm Machine Learning job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 75% Full Time, 23% Part Time, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $42,584 per year, or $20.5 per hour.

Lead Data Scientist- IBM Watson

Fusemachines

Manhattan, NY • On-site

Full-time

Re-posted 14 days ago

Job description

Job Summary:
Fusemachines is a global provider of enterprise AI products and services, on a mission to democratize AI. The Lead Data Scientist will design and implement data-driven solutions to complex business problems while leading a team of data scientists and collaborating with cross-functional teams.
Responsibilities:
• Lead a team of data scientists to develop innovative solutions to complex business problems. Mentor and develop the skills of junior data scientists and provide feedback and guidance to help them improve their work
• Collaborate with cross-functional teams, including business stakeholders, product managers, software engineers, and data engineers to develop and implement data-driven solutions
• Assess the business needs of clients and identify areas where AI can be used to improve processes, reduce costs, or increase revenue
• Design and implement statistical models, machine learning algorithms, predictive analytics models, and agentic systems to solve business problems
• Communicate technical insights and recommendations to non-technical stakeholders in a clear and concise manner
• Stay up-to-date with the latest developments in data science, machine learning, and artificial intelligence, and apply new technologies and techniques to solve business problems
• Responsible for developing, implementing, and managing end-to-end machine learning pipelines. This will involve building, deploying, and maintaining machine learning models, as well as ensuring data quality and system stability
Qualifications:
Required:
• Education: Bachelor's, Master's, PhD, or advanced training in applied mathematics, engineering, computer science, or a similar related field
• Experience: 6+ years of total experience in Data Science, Machine Learning & Generative AI
• Cloud Computing: 4+ years of hands-on experience with AWS, including deep expertise in deploying models and managing compute environments
• IBM WatsonX: 2+ years of hands-on experience with IBM WatsonX
• Agentic AI Tools: Experience with LangGraph, Google ADK or similar
• Agentic Architectures: Experience with advanced RAG & multi-agent systems
• Programming: Strong programming skills in languages such as Python, R, C++, and SQL
• Frameworks: Hands-on experience with ML frameworks, such as PyTorch or TensorFlow
• Leadership: Experience leading data science teams and managing multiple projects simultaneously
• Soft Skills: Strong problem-solving skills, attention to detail, and excellent communication skills (both written and verbal)
Company:
Fusemachines is an enterprise AI services and solutions provider that brings AI education, products, and jobs to underserved communities. Founded in 2013, the company is headquartered in New York, USA, with a team of 201-500 employees. The company is currently Growth Stage.

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