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Software Engineer Ml Jobs (NOW HIRING)

Software Technology Inc

Platform Software Engineer

... Engineer, ML DevOps Engineer, or Data Engineer (or equivalent) Fluency in Python Experience writing production level code Expert knowledge of designing software systems and production high-quality ...

Cadence

Lead Software Engineer, ML

San Jose, CA · On-site

... software engineering background with emphasis on C/C++, Python, Linux-based development • Experience with ML/DL frameworks like PyTorch • Understanding of LLM/Agentic AI Company : Cadence is a ...

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 ...

OpenReq

Software Engineer, ML Performance

Cupertino, CA · On-site

$172K/yr

They are seeking a Software Engineer, ML Performance to work closely with hardware and software teams to identify and mitigate performance bottlenecks in their custom-built AI hardware.

Cleerly

Sr. Software Engineer - ML Systems

Denver, CO

$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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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
Platform Software Engineer

Platform Software Engineer

Software Technology Inc

Remote

Other

Posted 6 days ago

Job description

Platform Software Engineer

Costa Mesa, CA (remote)

6-12+ month contract

4+ years of experience in software engineering

Strong software engineering and computer science background

Experience building end-to-end systems as a Platform Engineer, ML DevOps Engineer, or Data Engineer (or equivalent)

Fluency in Python

Experience writing production level code

Expert knowledge of designing software systems and production high-quality code

Strong experience developing micro services

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