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Ml Inference Jobs (NOW HIRING)

Third Way Health

AI / ML Engineer

Cambridge, MA · On-site

Develop predictive, real-time analytics systems that combine streaming data, ML inference, and event-driven triggers to surface insights and automate actions at scale. * Implement and maintain end-to ...

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Ml Inference information

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$37.5K

$122.7K

$196.5K

How much do ml inference jobs pay per year?

As of Jun 24, 2026, the average yearly pay for ml inference in the United States is $122,738.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,500.00 and $136,000.00 per year, depending on experience, location, and employer.

What is ML inference?

ML inference refers to the process of using a trained machine learning model to make predictions or decisions based on new data. After a model has been trained on historical data, inference is the phase where that model is deployed and used in real-world applications, such as recognizing speech, detecting objects in images, or recommending products. The focus in ML inference is on speed, efficiency, and scalability to ensure quick predictions, often in real time. This process is critical for practical applications like mobile apps, web services, and embedded systems. Optimizing inference involves reducing latency, memory usage, and computational requirements.

What is the difference between Ml Inference vs Data Scientist?

AspectML InferenceData Scientist
Required CredentialsKnowledge of machine learning models, programming skillsDegree in data science, statistics, or related fields
Work EnvironmentDeploying models in production, real-time data processingData analysis, model development, research
Industry UsageAI product deployment, software companiesResearch institutions, tech firms, consulting

ML Inference focuses on deploying trained models to make predictions on new data, often in real-time. Data Scientists develop and analyze models, working primarily in research and development. While both roles require understanding of machine learning, ML Inference emphasizes deployment and operationalization, whereas Data Scientists focus on model creation and analysis.

Which 3 jobs will survive AI?

For ML Inference roles, jobs that require complex problem-solving, creativity, and emotional intelligence are more likely to persist, such as data scientists, AI ethics specialists, and machine learning engineers. These roles involve tasks that are difficult to automate and often require specialized skills, domain knowledge, and critical thinking. Continuous learning and expertise in AI tools and programming languages like Python or TensorFlow can also enhance job security in this field.

What engineers make $500,000?

Senior machine learning engineers with extensive experience, specialized skills in deep learning, and strong industry demand can earn $500,000 or more annually, especially in high-cost-of-living areas or within top tech companies. Achieving this level typically requires advanced degrees, certifications, and a proven track record of impactful projects.

What is a $900,000 AI job?

A $900,000 AI job typically refers to high-level roles in artificial intelligence, such as senior machine learning engineers or AI research directors, often requiring advanced skills in deep learning, data science, and experience with tools like TensorFlow or PyTorch. These positions usually involve leadership responsibilities, strategic planning, and may require multiple years of specialized experience or advanced degrees.

Is ML a high paying job?

Machine Learning (ML) inference roles are generally well-paid due to the specialized skills required, such as knowledge of algorithms, programming, and data analysis. Salaries vary based on experience, location, and industry, but they tend to be higher than average for tech positions. Advanced roles often require proficiency with tools like TensorFlow or PyTorch and may include certifications or advanced degrees.

What are some common challenges faced by ML Inference Engineers when deploying models to production?

ML Inference Engineers often encounter challenges such as optimizing model latency and throughput to meet production requirements, ensuring compatibility with diverse hardware environments, and managing model versioning and updates without disrupting service. Additionally, balancing resource utilization and inference accuracy while monitoring real-time performance metrics is crucial. Collaboration with data scientists, DevOps, and software engineers is typically essential to streamline deployment and maintain robust, scalable inference pipelines.

What are the key skills and qualifications needed to thrive in ML Inference, and why are they important?

To thrive in ML Inference, you need a solid background in machine learning principles, programming (Python or C++), and experience with deploying models at scale, often supported by a degree in computer science or a related field. Familiarity with frameworks and tools such as TensorFlow, PyTorch, ONNX, and cloud platforms like AWS SageMaker or Google AI Platform is typically required. Strong problem-solving skills, attention to detail, and effective communication are crucial soft skills for collaborating with multidisciplinary teams and optimizing model performance. These skills ensure efficient, scalable, and reliable deployment of machine learning solutions in real-world applications.
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Ml Inference jobs near you
Staff Backend Engineer, ML Inference Systems

Staff Backend Engineer, ML Inference Systems

Unity Technologies

Mountain View, CA • On-site

Full-time

Medical, Life, Retirement, PTO

Posted 16 days ago

Job description

The opportunity
Every day, we connect billions of players with the games and experiences they love.
Our Vector Gamer AI team sits at the heart of that mission, governing ad ranking and bidding decisions across billions of daily impressions, where large-scale machine learning and real-world impact converge at scale.
We're hiring a Staff Backend Engineer to build and operate the infrastructure those models depend on. You'll design and operate the distributed systems that power billions of daily decisions, with a focus on the performance, reliability, and scalability of inference systems.
Join us and help influence how billions of gaming experiences are discovered, monetized, and how creators are rewarded.
What you'll be doing
  • Design, develop, and deploy production-grade backend services and distributed systems powering large-scale online model inference at billions of daily requests
  • Drive technical direction of our inference platform, with a focus on low-latency, high-throughput serving infrastructure
  • Partner with ML engineers to ensure online serving infrastructure scales with growing model complexity and inference volumes, without compromising latency or throughput
  • Ensure the reliability, scalability, and efficiency of our systems in production using monitoring and observability tools like Prometheus and Grafana
  • Manage and optimize cloud infrastructure on GCP, orchestrating workloads with Kubernetes across a high-scale production environment
  • Promote and implement best practices for backend service development, testing, deployment, and monitoring (DevOps, SRE)

What we're looking for
  • 5+ years designing, deploying, and maintaining distributed systems at scale
  • Expertise in Golang for building high-performance, low-latency backend infrastructure
  • Hands-on experience with cloud infrastructure on GCP and workload orchestration with Kubernetes
  • Strong grounding in monitoring and observability tooling, including Prometheus and Grafana
  • Experience in ad tech, recommender systems, real-time personalization, or other performance-critical domains
  • Familiarity with microservice architectures, containerization (Docker), and CI/CD best practices
  • Familiarity with machine learning platforms, workflows, and serving infrastructure

You might also have
  • Experience with ML inference servers like NVIDIA Triton Inference Server
  • Familiarity with auction mechanics or bidding systems in an ad tech context
  • Experience embracing AI as a strategic advantage in engineering, following established best practices for code quality and security

Additional information
  • Relocation support is not available for this position

Benefits
At Unity, we want our team members to thrive. We offer a wide range of benefits designed to support well-being and work-life balance.
Please note: Benefits eligibility, specific offerings, and coverage vary based on the country and employment status.
While specific benefits vary, here are some of the ways we strive to take care of our eligible team members globally: Comprehensive health, life, and disability insurance | Commute subsidy | Employee stock ownership | Competitive retirement/pension plans | Generous vacation and personal days | Support for new parents through leave and family-care programs | Office food snacks | Mental Health and Wellbeing programs and support | Employee Resource Groups | Global Employee Assistance Program | Training and development programs | Volunteering and donation matching program
Life at Unity
Unity [NYSE: U] is the world's leading game engine, powering play for more than 3 billion consumers each month. The top mobile games in the world, the most played PC indie titles, the most innovative console games, and virtually all of the top XR and Web Games are developed, deployed, and grown in Unity. Unity also enables teams across industries like automotive, manufacturing, and healthcare to design, simulate, and collaborate in 3D - closing the gap between ideas and reality. For more information, please visit www.unity.com.
Unity is a proud equal opportunity employer. We are committed to fostering an inclusive, innovative environment and celebrate our employees across age, race, color, ancestry, national origin, religion, disability, sex, gender identity or expression, sexual orientation, or any other protected status in accordance with applicable law. Our differences are strengths that enable us to support the growing and evolving needs of our customers, partners, and collaborators. If you have a disability that means there are preparations or accommodations we can make to help ensure you have a comfortable and positive interview experience, please fill out this form to let us know.
This position requires the incumbent to have a sufficient knowledge of English to have professional verbal and written exchanges in this language since the performance of the duties related to this position requires frequent and regular communication with colleagues and partners located worldwide and whose common language is English.
Headhunters and recruitment agencies may not submit resumes/CVs through this website or directly to managers. Unity does not accept unsolicited headhunter and agency resumes. Unity will not pay fees to any third-party agency or company that does not have a signed agreement with Unity.
Your privacy is important to us. Please take a moment to review our Prospect Privacy Policy and Applicant Privacy Policy. Should you have any concerns about your privacy, please contact us at DPO@unity.com.
#SEN #LI-AR1
*Note: This range reflects the anticipated base salary for this position. Beyond base salary, this role may be eligible for equity awards and participation in our company incentive plans (such as annual discretionary bonuses or sales commissions). The final offer amount will depend on several factors, including geographic location and the candidate's relevant experience, professional background, and skill set.
Gross pay salary
$192,600-$305,600 USD

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