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Ml Net Jobs (NOW HIRING)

Proconex

AI/ML Engineer - Vision AI

Royersford, PA · On-site

$103K - $142K/yr

Mask R-CNN, ResNet, U-Net) * Knowledge of object and anomaly detection (Autoencoders, FastFlow ... Understanding of the full ML / AI lifecycle Preferred Qualifications * Experience with real-time ...

Proconex

AI/ML Engineer - Vision AI

Royersford, PA

$103K - $142K/yr

Mask R-CNN, ResNet, U-Net) * Knowledge of object and anomaly detection (Autoencoders, FastFlow ... Understanding of the full ML / AI lifecycle Preferred Qualifications * Experience with real-time ...

Proconex

AI/ML Engineer - Vision AI

Royersford, PA

$103K - $142K/yr

Mask R-CNN, ResNet, U-Net) * Knowledge of object and anomaly detection (Autoencoders, FastFlow ... Understanding of the full ML / AI lifecycle Preferred Qualifications * Experience with real-time ...

Periodic Labs

ML Systems Engineer

Menlo Park, CA · On-site

$30K - $400K/yr

... versa The net result: high-throughput, fault-tolerant training and inference systems tightly ... Profiling and benchmarking distributed ML systems to identify and eliminate bottlenecks across ...

Periodic Labs

ML Systems Engineer

Menlo Park, CA

$300K - $400K/yr

... versa The net result: high-throughput, fault-tolerant training and inference systems tightly ... Profiling and benchmarking distributed ML systems to identify and eliminate bottlenecks across ...

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How much do ml net jobs pay per hour?

As of Jun 13, 2026, the average hourly pay for ml net in the United States is $53.73, according to ZipRecruiter salary data. Most workers in this role earn between $46.39 and $61.30 per hour, depending on experience, location, and employer.

What is an ML.NET job?

An ML.NET job typically involves developing and deploying machine learning models using Microsoft's ML.NET framework. Professionals in this role work with .NET applications, integrating ML capabilities into software solutions. They often preprocess data, train models, and optimize performance for real-world applications. Experience with C#, .NET, and data science principles is usually required.

Is ML.NET better than Python?

ML.NET is a machine learning framework designed for .NET developers to build and integrate ML models using C# or F#. Python is a widely used programming language with extensive libraries like TensorFlow and scikit-learn for machine learning. The choice depends on the development environment and project requirements, with Python generally offering more flexibility and a larger ecosystem for data science and ML tasks.

What are the typical responsibilities of an ML .NET Engineer on a development team?

As an ML .NET Engineer, your primary responsibilities include designing, building, and integrating machine learning models within the .NET framework, often using ML.NET and related Microsoft technologies. You will collaborate closely with software developers, data engineers, and product managers to ensure models are production-ready, scalable, and aligned with business needs. Daily tasks may involve data preprocessing, model training and evaluation, optimizing performance, and maintaining model pipelines. In many organizations, ML .NET Engineers also contribute to code reviews, mentoring, and continuous improvement initiatives focused on machine learning best practices.

Is .NET developer a good career?

.NET developers are in demand due to the widespread use of Microsoft technologies in enterprise applications. The role typically requires proficiency in C# and related tools, and offers opportunities for career growth in software development, system architecture, and cloud integration. Job stability and salary potential are generally favorable for skilled .NET developers.

What are the key skills and qualifications needed to thrive in the Ml Net position, and why are they important?

To thrive as an ML .NET (Machine Learning .NET) Engineer, a strong background in machine learning concepts, C# programming, and the Microsoft .NET ecosystem is essential, often backed by a degree in computer science or related fields. Experience with ML.NET, Azure Machine Learning, and version control systems like Git is highly valued, and certifications in Microsoft technologies can be advantageous. Problem-solving, analytical thinking, and the ability to communicate complex technical concepts to non-technical stakeholders are valuable soft skills for success in this role. These skills and qualities are critical for effectively developing, deploying, and maintaining robust machine learning solutions within .NET environments.

Which 5 jobs will survive AI?

For ML Net professionals, roles that require complex problem-solving, creativity, and human interaction are more likely to survive AI automation. These include data scientists, AI ethics specialists, machine learning engineers, cybersecurity analysts, and AI product managers. These jobs often require advanced technical skills, domain expertise, and adaptability to evolving technologies.

Is ML a high paying job?

Machine Learning (ML) roles are generally considered high-paying within the tech industry due to the specialized skills required, such as programming, data analysis, and knowledge of algorithms. Salaries vary based on experience, location, and company size but tend to be above average compared to many other professions in technology.
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Ml Net jobs near you
Infographic showing various Ml Net job openings in the United States as of June 2026, with employment types broken down into 100% Full Time. Highlights an 67% In-person, and 33% Remote job distribution, with an average salary of $111,761 per year, or $53.7 per hour.
Senior Product Manager, AI & ML Platform

Senior Product Manager, AI & ML Platform

Spring Health

Seattle, WA • On-site, Remote

$150K - $196K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 8 days ago

Job description

Our mission: to eliminate every barrier to mental health.
At Spring Health, we're on a mission to revolutionize mental healthcare by removing every barrier that prevents people from getting the help they need, when they need it. Our clinically validated technology,Precision Mental Healthcare, empowers us to deliver the right care at the right time-whether it's therapy, coaching, medication, or beyond-tailored to each individual's needs.
We proudly partner with over 450 companies, from startups to multinational Fortune 500 corporations, as a leading provider of mental health service, providing care for 10 million people. Our clients include brands you use and know like Microsoft, Target, and Delta Airlines, all of whom trust us to deliver best-in-class outcomes for their employees globally. With our innovative platform, we've been able to generate a net positive ROI for employers and we are the only company in our category to earn external validation of net savings for customers.
We have raised capital from prominent investors including Generation Investment, Kinnevik, Tiger Global, Northzone, RRE Ventures, and many more. Thanks to their partnership and our latest Series E Funding, our current valuation has reached $3.3 billion. We're just getting started-join us on our journey to make mental healthcare accessible to everyone, everywhere.
Reporting to the Senior Director of Product, Customer Value, you will be instrumental in defining and executing the vision for a scalable, secure, and extensible AI/ML foundation. You will build the core machine learning infrastructure and developer platform that powers intelligent features across the company, and enables product teams to rapidly develop, evaluate, deploy, and monitor AI solutions with confidence.
Please note that this is a hybrid role based in Seattle, with an expectation to be in the office 2-3 days per week at our 255 King St location. Candidates must be based in the Seattle metro area or able to relocate independently within 90 days of their start date. Occasional travel will be required for team on-sites.
What you'll do:
  • Shape and drive the AI/ML platform strategy and roadmap. Advance the long-term vision for our core ML infrastructure and AI developer platform, ensuring it enables rapid experimentation, safe deployment, and scalable production use across all product teams.
  • Lead continuous discovery with feature teams. Run an ongoing discovery motion with product, clinical, and engineering teams to deeply understand emerging AI use cases, pain points, and workflow gaps; translate those insights into a clear, prioritized roadmap that balances immediate enablement needs with long-term platform scalability and technical strategy.
  • Align platform investments to business impact. Prioritize infrastructure initiatives based on customer value, scalability, and ROI, ensuring the platform supports enterprise-grade performance, security, and cost efficiency.
  • Define platform solutions in close partnership with Engineering leadership. Collaborate with engineering managers to translate ambiguous AI/ML needs into well-scoped, technically sound platform capabilities, with clear problem statements, success metrics, definition of done, and thoughtful rollout and enablement plans that drive strong adoption among internal developers.

What success looks like:
  • Establish clear service standards for the AI/ML platform and consistently improve performance, stability, and scalability.
  • Build feedback loops with internal teams and measurably improve satisfaction by reducing friction and increasing self-serve capabilities.
  • Expand access to high-value data and platform capabilities while reducing the infrastructure burden on feature teams, enabling them to ship impactful AI features more quickly.

What you'll bring:
  • 4+ years of Product Management experience, including ownership of highly technical platforms, infrastructure, or developer-facing products.
  • Demonstrated experience partnering deeply with Engineering to ship scalable, reliable systems in production environments.
  • Strong understanding of AI/ML systems and workflows (e.g., model lifecycle, evaluation, deployment, observability), with the ability to translate complex technical concepts into clear product direction.
  • Track record of driving roadmap clarity in ambiguous, fast-moving spaces and delivering measurable outcomes.
  • Experience running continuous discovery with internal users and translating feedback into high-impact platform improvements.
  • Ability to define clear success metrics, service standards, and rollout strategies that drive adoption.
  • Excellent cross-functional communication skills, with the ability to influence senior technical stakeholders without formal authority.
  • Prior machine learning engineering experience is preferred but not required

The target base salary range for this position is $150,000 - 196,880, and is part of a competitive total rewards package including equity and benefits. Individual pay may vary from the target range and is determined by a number of factors including experience, location, internal pay equity, and other relevant business considerations. We review all employee pay and compensation programs annually using Radford Global Compensation Databaseat minimum to ensure competitive and fair pay.
Benefits provided by Spring Health:
Note: We have even more benefits than listed here and below, your recruiter will provide more in-depth information as you continue in the interview process. Benefits are subject to individual plan requirements and eligibility criteria.
  • Health, Dental, Vision benefits start on your first day at Spring. You and your dependents also receive access to One Medicalaccounts HSA and FSA plans are also available, with Spring contributing up to $1K for HSAs, depending on your plan type.
  • Employer sponsored 401(k) match of up to 2% for retirement planning
  • A yearly allotment of no cost visits to the Spring Health network of therapists, coaches, and medication management providers for you and your dependents.
  • We offer competitive paid time off policies including vacation, sick leave and company holidays.
  • At 6 months tenure with Spring, we offer parental leave of 18 weeks for birthing parents and 16 weeks for non-birthing parents.
  • Access to Noom, a weight management program-based in psychology, that's tailored to your unique needs and goals.
  • Access to fertility care support through Carrot, in addition to $4,000 reimbursement for related fertility expenses.
  • Access toWellhub, which connects employees to the best options for fitness, mindfulness, nutrition, and sleep in one subscription
  • Access to BrightHorizons, which provides sponsored child care, back-up care, and elder care
  • Up to $1,000 Professional Development Reimbursement a year.
  • $200 per year donation matching to support your favorite causes.

Not sure if you meet every requirement? Research shows that women and people from historically underrepresented communities often hesitate to apply for roles unless they meet every qualification compared to other similarly-qualified candidates. At Spring Health, we are committed to fostering a workplace where everyone feels valued, empowered, and supported to Thrive. If this role excites you, we encourage you to apply.
Our privacy policy: https://springhealth.com/privacy-policy/
Spring Health is proud to be an equal opportunity employer. We do not discriminate in hiring or any employment decision based on race, color, religion, national origin, age, sex, marital status, ancestry, disability, genetic information, veteran status, gender identity or expression, sexual orientation, pregnancy, or other applicable legally protected characteristic. We also consider qualified applicants regardless of criminal histories, consistent with applicable legal requirements. Spring Health is also committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans. If you have a disability or special need that requires accommodation, please let us know.

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