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Software Engineer Ml Jobs (NOW HIRING)

Afresh

Software Engineer, ML Platform

$130K - $196K/yr

... engineers, data scientists, or applied scientists on large-scale software projects involving machine learning models. * You possess a genuine curiosity about ML modeling (e.g., demand forecasting ...

Specter

Software Engineer - ML Infrastructure

San Francisco, CA · On-site

$203K - $241K/yr

... ML. * Experience with distributed training frameworks (PyTorch DDP, DeepSpeed, Ray) and GPU cluster management. * Strong software engineering skills in Python and systems languages (C++, Rust) for ...

Cleerly

Sr. Software Engineer - ML Systems

Denver, CO · On-site

$176K - $206K/yr

About the Opportunity We are seeking a Senior Software Engineer to design, build, deploy, monitor, and optimize production-ready ML services in regulated healthcare. You will work hands-on to package ...

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$63.5K

$147.5K

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How much do software engineer ml jobs pay per year?

As of Jun 5, 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 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.

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.

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.
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Software Engineer Ml jobs near you
Infographic showing various Software Engineer Ml job openings in the United States as of May 2026, with employment types broken down into 1% Internship, 95% Full Time, 1% Part Time, and 3% Contract. Highlights an 88% Physical, 3% Hybrid, and 9% Remote job distribution, with an average salary of $147,524 per year, or $70.9 per hour.
Senior Software Engineer - ML Services

Senior Software Engineer - ML Services

AI Fund

Mountain View, CA • On-site

$145K - $192K/yr

Full-time

Posted 28 days ago

Job description

Job Summary:
LandingAI is an AI-native company focused on transforming unstructured data into structured, computable information. The Senior Software Engineer - ML Services will design and maintain AI-powered applications while collaborating closely with Machine Learning Engineers to drive innovation and improve ML development processes.
Responsibilities:
• Be a driving force for the team's agentic coding practice - establishing patterns for spec-driven development, context engineering, and multi-agent orchestration that compound team output.
• Design, develop, and maintain AI-powered applications and services, focusing on high availability, performance, and reliability.
• Work closely with Machine Learning Engineers, building AI capabilities from early R&D prototyping to scalable operation in multiple production stacks.
• Build ML services designed for low-latency or high-throughput, and optimized for high cost efficiency.
• Lead cross-functional initiatives, collaborating with Machine Learning Engineers, Product Managers, and other teams to align technical solutions with business needs.
• Drive innovation by making strategic technical decisions, setting best practices, and mentoring engineers to elevate the team’s technical bar.
• Improve ML development process by enhancing the internal ML platform, facilitating data sourcing, and enabling ML observability for deployed services.
Qualifications:
Required:
• Fluency with agentic coding tools (Claude Code, Codex or equivalent). Experience writing effective specs, managing repo context, and reviewing/verifying agent output.
• 5+ years of experience in software development, with a strong backend and ML engineering background.
• Experience working with cloud native technologies (Docker, Kubernetes).
• Experience working with cloud platforms (AWS, GCP, or Azure).
• Experience with building ML systems, from early prototype, to operating at scale in production.
• Strong software architecture skills, with experience designing and scaling distributed systems and cloud-based applications.
• Experience mentoring engineers and contributing to team-wide technical direction.
• Strong communication skills, with the ability to translate technical challenges into business impact.
Preferred:
• Experience with ML frameworks like pytorch.
• Experience with serving ML models and LLMs using frameworks like vllm.
• Experience with developer-facing products and building intuitive APIs.
Company:
AI Fund is a VC firm made up of AI pioneers, operators, entrepreneurs, and investors, supported by LPs such as NEA, Sequoia and Greylock. Founded in 2017, the company is headquartered in Palo Alto, USA, with a team of 11-50 employees. The company is currently Early Stage.

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