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Senior Staff Machine Learning Engineer Jobs (NOW HIRING)

Avride

Senior / Staff Machine Learning Engineer

Austin, TX · On-site

$124K - $171K/yr

About the role We are hiring experienced Machine Learning Engineers across Senior, Staff, and Principal levels. to site onsite in Austin, Texas. Whether you're a strong individual contributor ready ...

Avride

Senior / Staff Machine Learning Engineer

Austin, TX

$124K - $171K/yr

About the role We are hiring experienced Machine Learning Engineers across Senior, Staff, and Principal levels. to site onsite in Austin, Texas. Whether you're a strong individual contributor ready ...

Avride

Senior / Staff Machine Learning Engineer

Austin, TX · On-site

$124K - $171K/yr

They are seeking experienced Machine Learning Engineers to drive the development and deployment of ... At Staff and Principal levels, you will drive alignment across functions, mentor junior and senior ...

Averity

Staff Machine Learning Engineer

Manhattan, NY · On-site

$170K - $215K/yr

Staff Machine Learning Engineer - AI Products Location: Hybrid in NYC (Bryant Park Office) Salary Range: $170,000 - $215,000 A leading health and wellness technology company is searching for a Staff ...

Etsy

Senior Staff Machine Learning Engineer

New York, NY · On-site +1

$245K - $319K/yr

We are looking for a Senior Staff Software Engineer, Machine Learning to be a pivotal technical leader in architecting the next generation of AI/ML models and systems that connect buyers and sellers ...

Paylocity

Staff Machine Learning Engineer

As a Staff Machine Learning Engineer in Product & Technology, you will help Paylocity build and deploy Machine Learning solutions, to help our teams build better products faster, more reliably, and ...

Intuit

Staff Machine Learning Engineer

Mountain View, CA

$202K - $274K/yr

Come join Intuit as a Staff Machine Learning Engineer! In this role, you'll work alongside AI scientists and machine learning engineers to create AI-powered experiences. You'll be expected to help ...

Intuit

Staff Machine Learning Engineer

Mountain View, CA

$202K - $274K/yr

Overview Come join Intuit as a Staff Machine Learning Engineer! In this role, you'll work alongside AI scientists and machine learning engineers to create AI-powered experiences. You'll be expected ...

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Senior Staff Machine Learning Engineer information

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$59.5K

$126.6K

$183.5K

How much do senior staff machine learning engineer jobs pay per year?

As of Jul 29, 2026, the average yearly pay for senior staff machine learning engineer in the United States is $126,557.00, according to ZipRecruiter salary data. Most workers in this role earn between $104,500.00 and $143,500.00 per year, depending on experience, location, and employer.

What are the primary challenges a Senior Staff Machine Learning Engineer faces when leading large-scale ML projects?

Senior Staff Machine Learning Engineers often navigate complex challenges such as aligning cross-functional teams, ensuring model scalability, and maintaining data integrity across evolving pipelines. They are responsible for setting technical direction, mentoring junior engineers, and driving collaboration between data scientists, software engineers, and product managers. Balancing hands-on technical work with high-level architectural decisions, while also keeping up with rapid advancements in the field, is key to success in this role.

What does a Senior Staff Machine Learning Engineer do?

A Senior Staff Machine Learning Engineer leads the design, development, and deployment of complex machine learning systems within an organization. They work closely with cross-functional teams to identify business challenges that can be addressed with machine learning and guide the technical strategy for implementing solutions. Their responsibilities often include mentoring junior engineers, setting best practices, overseeing large-scale projects, and ensuring models are robust, scalable, and ethically implemented. Additionally, they may contribute to research and development, staying up-to-date with the latest advancements in the field.

What is the difference between Senior Staff Machine Learning Engineer vs Machine Learning Engineer?

AspectSenior Staff Machine Learning EngineerMachine Learning Engineer
CredentialsBachelor's/Master's/PhD in CS, AI, or related; experience in ML frameworksBachelor's/Master's in CS, AI, or related; some experience in ML
Work EnvironmentLeadership roles, cross-team collaboration, strategic planningImplementation, model development, experimentation
Industry UsageTech companies, research labs, large enterprisesStartups, tech firms, research projects

The Senior Staff Machine Learning Engineer typically holds a more senior, strategic role with leadership responsibilities, while the Machine Learning Engineer focuses on developing and deploying ML models. Both roles require strong technical skills, but the senior position involves guiding projects and mentoring teams.

What are the key skills and qualifications needed to thrive as a Senior Staff Machine Learning Engineer, and why are they important?

To thrive as a Senior Staff Machine Learning Engineer, you need deep expertise in machine learning algorithms, statistical analysis, software engineering, and a relevant advanced degree (often MS or PhD). Mastery of tools such as Python, TensorFlow, PyTorch, distributed computing frameworks, and experience with cloud platforms is typically required. Strong leadership, communication, and project management skills distinguish top performers in this role. These abilities are crucial for designing scalable ML solutions, leading teams, and driving impactful business outcomes.
More about Senior Staff Machine Learning Engineer jobs
What cities are hiring for Senior Staff Machine Learning Engineer jobs? Cities with the most Senior Staff Machine Learning Engineer job openings:
What states have the most Senior Staff Machine Learning Engineer jobs? States with the most job openings for Senior Staff Machine Learning Engineer jobs include:
What job categories do people searching Senior Staff Machine Learning Engineer jobs look for? The top searched job categories for Senior Staff Machine Learning Engineer jobs are:
Senior Staff Machine Learning Engineer jobs near you
Infographic showing various Senior Staff Machine Learning Engineer job openings in the United States as of July 2026, with employment types broken down into 96% Full Time, 1% Part Time, and 3% Contract. Highlights an 87% Physical, 5% Hybrid, and 8% Remote job distribution, with an average salary of $126,557 per year, or $60.8 per hour.
Senior Staff Machine Learning Engineer

Senior Staff Machine Learning Engineer

Intuit

Mountain View, CA • On-site

$65.25 - $84/hr

Full-time

Posted 4 days ago

Intuit rating

8.4

Company rating: 8.4 out of 10

Based on 90 frontline employees who took The Breakroom Quiz

87th of 246 rated software companies

Job description

Come join Intuit as a Senior Staff Machine Learning Engineer (MLE).
Senior Staff MLEs deliver end-to-end AI solutions that span multiple domains and products, influencing the strategic direction of machine learning and AI across the company. You will identify cross-cutting opportunities, set technical direction for complex systems, and deliver scalable, responsible AI-driven experiences that unlock customer and business value at Intuit scale.
In this role, you'll be expected to define and evolve ML architecture, guide multiple teams, and drive execution excellence across the full ML lifecycle-from experimentation to production. You'll partner closely with AI scientists, product engineers, and business leaders to solve high-impact problems and pioneer new capabilities that advance Intuit's AI-native platform.
Responsibilities
Technical Craft
  • Lead the architectural design of complex, cross-cutting ML systems and data platforms that serve multiple Intuit products.
  • Drive the adoption of AI-native design principles, ensuring that systems are built for adaptability, observability, and secure customer data usage.
  • Build and scale end-to-end ML solutions using cloud-native and open-source technologies (e.g., AWS, GCP, TensorFlow, PyTorch, Ray, Spark).
  • Define engineering standards, model governance, and MLOps best practices
  • across teams for training, deployment, monitoring, and continuous improvement.
  • Evaluate and integrate transformative technologies such as foundation models, retrieval-augmented generation (RAG), and LLM fine-tuning pipelines to accelerate product innovation.
  • Resolve deeply complex issues across domains, often requiring novel solutions or architectural evolution for long-term scalability.

Execution Excellence
  • Deliver within large-scale strategic initiatives, identifying systemic architectural gaps and leading their resolution across multiple teams.
  • Challenge roadmaps to achieve measurable outcomes in weeks-not months, while balancing technical risk, business priorities, and product velocity.
  • Establish clear execution boundaries and integration contracts across teams to accelerate delivery while maintaining quality.
  • Proactively monitor model and system performance, ensuring continuous improvement of reliability, fairness, and customer impact.
  • Champion experimentation at scale-defining hypotheses, success metrics, and iterative validation frameworks that balance speed with rigor.

Customer-Centric Outcomes
  • Translate emerging customer behaviors and business trends into bold ML-driven solutions that redefine customer experiences across Intuit's ecosystem.
  • Collaborate with Product and Design to frame and validate high-risk, high-impact hypotheses through MVPs and data-driven experimentation.
  • Lead initiatives that use customer signals, behavioral data, and competitive insights
  • to identify unmet needs and shape Intuit's AI roadmap.
  • Drive the development and deployment of models that directly improve measurable customer outcomes-conversion, engagement, trust, and satisfaction.
  • Balance rapid delivery with long-term technical sustainability, ensuring quality and performance at scale.

Accelerating Teams & the Organization
  • Act as a force multiplier, raising the technical bar across multiple ML and engineering teams (typically influencing 10-35 engineers).
  • Mentor and develop Staff and Senior MLEs, building a strong culture of learning, quality, and execution excellence.
  • Identify and drive resolution for cross-team bottlenecks-architectural, tooling, or communication-related-that limit productivity or scalability.
  • Build alignment across AI, product, and infrastructure teams to accelerate delivery of strategic initiatives.
  • Provide architectural guidance, influence design reviews, and serve as a key connector between product, data, and platform teams.
  • Champion diversity of thought and inclusive innovation within the ML and engineering community at Intuit.

Intuit provides a competitive compensation package with a strong pay for performance rewards approach. The expected base pay range for this position is:
Bay Area California: $214,000 - $289,500
This position will be eligible for a cash bonus, equity rewards and benefits, in accordance with our applicable plans and programs (see more about our compensation and benefits at ).
Pay offered is based on factors such as job-related knowledge, skills, experience, and work location. To drive ongoing pay equity for employees, Intuit conducts regular comparisons across categories of ethnicity and gender.
Qualifications
  • BS, MS, or PhD in Computer Science, Machine Learning, or a related technical field, or equivalent practical experience.
  • 8+ years of experience in software or ML engineering, with at least 3+ years at Staff level or equivalent leadership scope.
  • Proven track record of architecting and delivering production-scale ML systems that impact millions of users.
  • Expert in ML lifecycle management, feature engineering, and large-scale model deployment.
  • Deep hands-on experience with modern ML frameworks and distributed systems (TensorFlow, PyTorch, Spark, Ray, Kubernetes, MLflow, etc.).
  • Experience leading cross-functional initiatives spanning multiple product or platform.
  • Strong background in software engineering fundamentals: algorithms, distributed systems, data pipelines, and performance optimization.
  • Excellent communication and influence skills, capable of aligning technical direction with organizational strategy.
  • Familiarity with LLMs, GenAI, and applied responsible AI practices is a strong plus.

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Intuit provides a competitive compensation package with a strong pay for performance rewards approach. This position will be eligible for a cash bonus, equity rewards and benefits, in accordance with our applicable plans and programs (see more about our compensation and benefits at ). Pay offered is based on factors such as job-related knowledge, skills, experience, and work location. To drive ongoing fair pay for employees, Intuit conducts regular comparisons across categories of ethnicity and gender.
The expected base pay range for this position is:
Mountain View $220,500 - $298,500

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