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Software Engineer Ml Jobs (NOW HIRING)

Avride

Software Engineer - ML Platform

Austin, TX

We sit between Cloud Platform and ML engineers, turning low-level compute, storage, and networking primitives into an ML platform that teams actually use - scalable orchestration, distributed compute ...

Avride

Software Engineer - ML Platform

Austin, TX · On-site

We sit between Cloud Platform and ML engineers, turning low-level compute, storage, and networking primitives into an ML platform that teams actually use - scalable orchestration, distributed compute ...

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Software Engineer Ml information

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How much do software engineer ml jobs pay per year?

As of Jun 29, 2026, the average yearly pay for software engineer ml in the United States is $147,524.00, according to ZipRecruiter salary data. Most workers in this role earn between $120,000.00 and $173,000.00 per year, depending on experience, location, and employer.

What engineers make $500,000?

Senior software engineers, especially those working in high-demand areas like tech hubs or with expertise in machine learning, cloud computing, or specialized skills, can earn $500,000 or more annually through base salary, bonuses, and stock options. Achieving this level typically requires extensive experience, advanced technical skills, and often leadership responsibilities or working at large tech companies or startups with significant funding.

What does a Software Engineer, ML do?

A Software Engineer, ML (Machine Learning) designs, develops, and deploys software systems that use machine learning algorithms to solve complex problems. They work on tasks such as building data pipelines, training and testing machine learning models, and integrating these models into production applications. They collaborate closely with data scientists, product managers, and other engineers to ensure that ML systems are scalable, efficient, and meet business objectives. Their work often involves programming, data analysis, and staying up-to-date with the latest developments in AI and machine learning.

What are some common challenges faced by Software Engineers working in Machine Learning, and how can they be addressed?

Software Engineers in Machine Learning often encounter challenges such as managing large datasets, ensuring model accuracy, and keeping up with rapidly evolving frameworks and tools. Collaboration with data scientists and domain experts is essential to align technical solutions with business goals. Staying current through continuous learning and leveraging cloud-based platforms or MLOps practices can help streamline workflows and improve model deployment. Additionally, effective communication within cross-functional teams is crucial for addressing both technical and non-technical challenges.

Do ML engineers get paid well?

Machine Learning (ML) engineers typically earn high salaries due to their specialized skills in algorithms, data modeling, and programming languages like Python and TensorFlow. Compensation varies based on experience, location, and industry, but they generally receive above-average pay compared to other software engineering roles.

Which 5 jobs will survive AI?

Software engineers specializing in machine learning, AI system development, and data science are likely to continue thriving as these fields require complex problem-solving, creativity, and domain expertise that are difficult for AI to fully replicate. Roles involving AI model training, ethical oversight, and system integration will remain in demand due to their specialized knowledge and ongoing innovation needs.

What are the key skills and qualifications needed to thrive as a Software Engineer ML, and why are they important?

To thrive as a Software Engineer ML, you need strong proficiency in programming (especially Python), algorithms, machine learning theory, and a relevant degree in computer science or a related field. Experience with ML frameworks like TensorFlow or PyTorch, and familiarity with cloud computing platforms and version control systems are typically required. Analytical thinking, problem-solving, and effective communication skills help you stand out in collaborative and complex project environments. These skills are vital to efficiently develop, deploy, and maintain robust machine learning solutions that drive business value.

Are ML engineers still in demand?

ML engineers are currently in high demand due to the growth of artificial intelligence and machine learning applications across industries. They typically require skills in programming, data analysis, and frameworks like TensorFlow or PyTorch, and job opportunities are expected to remain strong as AI adoption expands.
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Software Engineer Ml jobs near you
Software Engineer, ML Infrastructure, Level 4

Software Engineer, ML Infrastructure, Level 4

Snap Inc.

Bellevue, WA • On-site

$194K - $230K/yr

Full-time

Posted yesterday

Key responsibilities

  • Design and optimize infrastructure systems for machine learning workloads at scale and drive reliability and efficiency improvements across Snapchat's ML Infrastructure.

  • Build and enhance feature generation and serving pipelines that power online inferencing and offline training data generation.

  • Develop high-performance inference systems to ensure fast and efficient AI model serving.

Job description

Job Summary:
Snap Inc is a technology company focused on improving communication through innovative products like Snapchat and AR technologies. The Software Engineer, ML Infrastructure will play a critical role in scaling ML infrastructure, optimizing systems, and driving innovations for Snapchat’s ranking and recommendation systems.
Responsibilities:
• Design and optimize infrastructure systems for machine learning workloads at scale and drive reliability and efficiency improvements across Snapchat’s ML Infrastructure
• Build and enhance feature generation and serving pipelines that power online inferencing and offline training data generation
• Develop high-performance inference systems to ensure fast and efficient AI model serving
• Build infrastructure to perform scalable ML model training, evaluation, and inference in the cloud
• Develop high-performance inference systems to ensure fast and efficient AI model serving
• Build comprehensive data management systems for scalable data collection, labeling, processing, and evaluation
• Work closely with ML engineers to deploy cutting-edge models into production
• Utilize AI tools and high velocity engineering workflows to design and ship scalable services while upholding rigorous standards for code correctness, security, and production ready quality code
Qualifications:
Required:
• Strong programming skills in Python, Java, Scala or C++
• Strong problem-solving skills with a focus on system performance, scalability, and efficiency
• Good understanding of distributed systems and the infrastructure components of large-scale ML
• Experience with big data processing frameworks such as Spark, Flink, or Ray
• Ability to collaborate and work well with others
• Proven track record of operating highly-available systems at significant scale
• Ability to proactively learn new concepts and apply them at work
• Adaptability in learning and applying evolving AI systems and tools to remain at the forefront of engineering trends and modern development practices
• Bachelor’s degree in a technical field such as computer science or equivalent experience
• 2+ years of post-Bachelor’s software development experience; or Master’s degree in a technical field + 1+ year of post-grad software development experience; or PhD in a relevant technical field
• Experience building large scale production machine learning systems, distributed systems or big data processing
Preferred:
• Masters/PhD in a technical field such as computer science or equivalent industry experience
• Experience working with ML Training platforms or optimizing AI model inference
• Familiarity with ML frameworks such as TensorFlow, PyTorch, Caffe2, Spark ML, scikit-learn, or related frameworks
Company:
Snap is a technology company. We believe the camera presents the greatest opportunity to improve the way people live and communicate. Founded in 2011, the company is headquartered in Santa Monica, USA, with a team of 5001-10000 employees. The company is currently Late Stage.

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