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Senior Machine Learning Researcher Jobs in Madison, WI

Senior Data Scientist What you will do Let's do this! Let's change the world! In this vital role ... Design, develop, and deploy first principles, machine learning, and hybrid models to optimize ...

Senior Research Scientist-Field Day

Madison, WI · On-site +1

$99K - $126K/yr

Its work bridges educational research, learning-game development, data science, and engagement with ... The Senior Research Scientist will provide scientific and strategic leadership for Field Day ...

Senior Technical Consultant

Madison, WI · On-site

$100K - $200K/yr

We are seeking a Senior Consultant to join our Customer Success team. In this role, you will be ... Machine Learning, Google Cloud, Application Integration, Database, Developer Tools, Management ...

Senior Software Engineer

Oregon, WI · On-site

$120 - $170/hr

... Machine Learning esp. in Natural Language Understanding, Machine Translation, Deep Neural Networks and related fields * Demonstrated ability to design, develop, and maintain robust applications using ...

... and researchers access to the data they need to take care of their patients and improve health ... Our team of data scientists, machine learning engineers, revenue cycle professionals, and certified ...

Showing results 41-60

Senior Machine Learning Researcher information

See Madison, WI salary details

$28.7K

$77.2K

$138.6K

How much do senior machine learning researcher jobs pay per year?

As of Aug 11, 2026, the average yearly pay for senior machine learning researcher in Madison, WI is $77,191.00, according to ZipRecruiter salary data. Most workers in this role earn between $50,400.00 and $99,300.00 per year, depending on experience, location, and employer.

What opportunities for collaboration typically exist for senior machine learning researchers within a company?

Senior Machine Learning Researchers frequently collaborate with cross-functional teams, including data engineers, software developers, and domain experts. This collaboration ensures that research insights are effectively translated into scalable solutions and integrated into products or services. Researchers often participate in brainstorming sessions, code reviews, and joint publications, fostering a culture of innovation and shared knowledge. These interactions not only drive the success of projects but also provide valuable learning experiences and networking opportunities.

What does a senior machine learning researcher do?

A Senior Machine Learning Researcher leads the development and application of advanced machine learning models to solve complex problems. They are responsible for designing experiments, analyzing large datasets, publishing research findings, and collaborating with engineering teams to implement solutions. Additionally, they mentor junior researchers, stay updated with the latest advancements in AI, and often contribute to setting the research agenda for their organization.

What is the difference between Senior Machine Learning Researcher vs Data Scientist?

AspectSenior Machine Learning ResearcherData Scientist
CredentialsAdvanced degrees in CS, ML, or related fieldsDegree in CS, statistics, or related fields; certifications optional
Work EnvironmentResearch labs, R&D teams, academiaBusiness analytics, product teams, startups
Industry UsageResearch-focused roles in tech, academia, R&DData analysis, business insights, product development
Search & Comparison IntentUnderstanding research vs applied roles in MLExploring data analysis careers and skills

While both roles involve working with data and machine learning, a Senior Machine Learning Researcher primarily focuses on developing new algorithms and advancing ML theory in research settings. In contrast, a Data Scientist applies existing models to analyze data, generate insights, and support business decisions. The roles differ mainly in their focus—research innovation versus practical application—though they share overlapping skills and credentials.

What are the key skills and qualifications needed to thrive as a senior machine learning researcher, and why are they important?

To thrive as a Senior Machine Learning Researcher, you need advanced knowledge in machine learning algorithms, statistical analysis, programming (typically in Python), and a relevant advanced degree such as a PhD or Master's in computer science or a related field. Experience with frameworks like TensorFlow or PyTorch, as well as familiarity with cloud computing platforms and research publication, is often required. Strong problem-solving, collaboration, and communication skills help you work effectively with cross-functional teams and present complex ideas clearly. These skills and qualities are essential for driving innovation, developing robust models, and translating research into practical, impactful solutions.
What are popular job titles related to Senior Machine Learning Researcher jobs in Madison, WI? For Senior Machine Learning Researcher jobs in Madison, WI, the most frequently searched job titles are:
What job categories do people searching Senior Machine Learning Researcher jobs in Madison, WI look for? The top searched job categories for Senior Machine Learning Researcher jobs in Madison, WI are:
Infographic showing various Senior Machine Learning Researcher job openings in Madison, WI as of August 2026, with employment types broken down into 1% As Needed, 66% Full Time, 30% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $77,191 per year, or $37.1 per hour.

Principal Consultant, Artificial Intelligence (AI) (Remote - US)

Medium

Oregon, WI • On-site

$170 - $190/hr

Other

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 4 days ago


Job description

Atmosera empowers businesses to redefine what’s possible with modern technology and human expertise. Our experience across Applications, Data & AI, DevOps, Security, and Microsoft Azure accelerates innovation, enhances security, and optimizes operational agility. As a Microsoft Partner with seven specializations and a member of the GitHub Advisory Board, Atmosera delivers integrated solutions that create business value.

Key Responsibilities
  • Client Discovery & AI Readiness Assessment
    • Lead structured discovery sessions (in‑person and virtual) with executive stakeholders and technical SMEs to assess current state AI, data, cloud, and automation architecture, business processes, decision points, operational pain areas, and organizational readiness, governance maturity, and risk posture for AI adoption.
    • Translate ambiguous client inputs into clear, actionable findings that inform both business and technical decisions.
    • Produce discovery outputs that support executive alignment and downstream architecture decisions.
  • Use Case Portfolio, ROI Stress Testing & Prioritization
    • Identify, define, and document AI use cases across business functions, including business value hypothesis, success metrics, technical feasibility, data dependencies, and delivery complexity.
    • Build a use case portfolio and conduct an ROI stress test, prioritizing measurable business impact, feasibility and risk, and time‑to‑value and scalability.
    • Create and present a priority matrix (impact × complexity × risk) and a sequenced AI adoption roadmap for executive decision making.
  • AI Architecture & Solution Design
    • Own the end‑to‑end architecture and design of complex AI, machine learning, and intelligent automation solutions, including generative and agentic AI architectures, predictive and supervised ML solutions, workflow automation and orchestration, and secure integration with enterprise systems and data sources.
    • Define reference architectures, design patterns, and guardrails that ensure solutions are secure, scalable, governable, and production‑ready.
    • Collaborate closely with AI Engineers, Platform Engineers, Data, Security, and Delivery teams to translate architectural intent into successful implementation.
  • AI Center of Excellence (CoE) Design & Enablement
    • Design and help establish AI Centers of Excellence for clients, including AI intake and qualification models, architecture and development standards, governance, responsible AI, and risk controls, and operating models for scaling AI across the organization.
    • Enable client teams with frameworks, artifacts, and guidance that allow the CoE to operate independently over time.
  • Platform & Ecosystem Expertise
    • Deep familiarity with the Microsoft AI ecosystem (Microsoft Foundry, Azure AI services, Azure Machine Learning, Microsoft Fabric, Copilot Studio, modern agent‑based AI approaches).
    • Comfortable architecting solutions on or translating architectures across AWS, Google Cloud Platform (GCP), and other multicloud environments; Microsoft Azure remains the primary stack.
  • Data & Machine Learning Foundations
    • Strong working knowledge of data management concepts (data quality, lineage, governance, lifecycle), feature engineering, and data readiness for ML.
    • Collaborate with internal and client data platform teams to design against data platforms without owning them.
    • Apply solid foundations in statistics and applied machine learning to ensure models are architected appropriately, and assumptions, limitations, and risks are well understood and communicated.
  • Executive Communication & Consulting Leadership
    • Lead business‑level and AI‑level conversations with C‑suite and senior leadership.
    • Translate complex technical architectures into clear business narratives tied to value, risk, and outcomes.
    • Provide trusted advisory guidance on AI strategy, operating models, and investment decisions.
    • Contribute to the development of repeatable consulting offers, assessments, and delivery frameworks.
Required Qualifications
  • 10+ years of consulting experience leading client discovery, workshops, and executive readouts.
  • Proven experience as an AI Architect, AI Solution Architect, or equivalent role.
  • Hands‑on experience as an AI Engineer or ML Engineer building real AI solutions of moderate to advanced complexity.
  • Strong architecture background across cloud, security, integration, and scalability.
  • Excellent written and spoken English.
Preferred Qualifications
  • Experience designing or operating AI Centers of Excellence.
  • Multicloud experience across Azure, AWS, and GCP.
  • Business management or business operations experience enabling strong understanding of client needs and constraints.
  • Spanish business‑professional fluency.
Salary

$170,000 – $190,000 a year

Benefits

Atmosera offers a comprehensive benefits package to support your well‑being and financial security.

  • Competitive salary commensurate with experience.
  • Generous 401(k) plan with 100% company match up to 4% of salary.
  • Performance‑based compensation with bonus potential.
  • 100% employer‑paid health, vision, and dental insurance for employees.
  • Company‑paid life, accidental death & dismemberment, and short‑ and long‑term disability insurance.
  • Generous paid time off (three weeks of PTO) and 11 paid holidays.
  • Paid community‑service leave.
  • Employee recognition and reward program.

This is a full‑time position in the United States with the ability to work from home or from one of our many U.S. offices if local.

EEO Statement

Atmosera is an equal‑opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. We do not discriminate based on race, religion, color, national origin, gender, sexual orientation, gender identity, age, veteran status, disability, or any other legally protected characteristics. All employment decisions are based on qualifications, merit, and business need.

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