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Software Engineer Ml Jobs (NOW HIRING)

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 ...

Liftoff

Software Engineer, ML Data

San Francisco, CA · On-site

$180K - $230K/yr

As a Software Engineer on the Machine Learning Data Platform team at Liftoff, you will: * Work with an experienced team of ML, Software, and Infrastructure Engineers that are building the ML platform ...

Worldpay

Senior ML Software Engineer

Atlanta, GA · On-site

$117K - $155K/yr

We are seeking an experienced Senior ML Software Engineer to join our Data Science Enablement team. You will be the primary software engineering expert for a product area, working as part of a cross ...

Cleerly

Sr. Software Engineer - ML Systems

They are seeking a Senior Software Engineer to design and optimize production-ready machine ... Responsibilities : • Design, build, and deploy scalable AI/ML services with clear service ...

Worldpay

Senior ML Software Engineer

Cincinnati, OH · On-site

$117K - $155K/yr

We are seeking an experienced Senior ML Software Engineer to join our Data Science Enablement team. You will be the primary software engineering expert for a product area, working as part of a cross ...

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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$63.5K

$147.5K

$205.5K

How much do software engineer ml jobs pay per year?

As of Aug 8, 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 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.

Are software engineer ML still in demand?

Software engineers specializing in machine learning are in high demand due to the growth of AI and data-driven applications. Skills in programming, data analysis, and frameworks like TensorFlow or PyTorch are valuable, and the role often requires staying current with evolving technologies. The demand is expected to continue as organizations increasingly adopt AI solutions.

What are the key skills and qualifications needed to thrive as a software engineer ML?

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.
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What cities are hiring for Software Engineer Ml jobs? Cities with the most Software Engineer Ml job openings:
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Software Engineer ML jobs near you
Infographic showing various Software Engineer Ml job openings in the United States as of August 2026, with employment types broken down into 89% Full Time, 7% Part Time, and 4% 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 Platform

Parafin, Inc

San Francisco, CA • On-site

$220K - $265K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Re-posted 4 days ago

Job description

About Us:
At Parafin, we're on a mission to grow small businesses.
Small businesses are the backbone of our economy, but traditional banks often don't have their backs. We build tech that makes it simple for small businesses to access the financial tools they need through the platforms they already sell on.
We partner with companies like DoorDash, Amazon, Worldpay, and Mindbody to offer fast and flexible funding, spend management, and savings tools to their small business users via a simple integration. Parafin takes on all the complexity of capital markets, underwriting, servicing, compliance, and customer service for our partners.
We're a tight-knit team of innovators hailing from Stripe, Square, Plaid, Coinbase, Robinhood, CERN, and more - all united by a passion for building tools that help small businesses succeed. Parafin is backed by prominent venture capitalists including GIC, Notable Capital, Redpoint Ventures, Ribbit Capital, and Thrive Capital. Parafin is a Series C company, and we have raised more than $194M in equity and $340M in debt facilities.
Join us in creating a future where every small business has the financial tools they need.
About The Position
We're looking for a software engineer to join Parafin's Infrastructure team and lead the evolution of our ML Platform. This role is critical to building reliable, scalable, and developer-friendly systems for model experimentation, training, evaluation, inference, and retraining that power underwriting and other ML-driven products for small businesses.
As a Software Engineer, you'll design, build, and maintain the core abstractions and platforms that let data scientists ship high-quality models to production-safely and quickly. You'll partner closely with Data Science and Platform Engineering, own the ML platform end-to-end, and develop batch and real-time underwriting infrastructure.
What You'll Do
  • Turn notebooks into software. Decompose data scientist training/inference notebooks into reusable, tested components (libraries, pipelines, templates) with clear interfaces and documentation.
  • Create developer-friendly ML abstractions. Build SDKs, CLIs, and templates that make it simple to define features, train/evaluate models, and deploy to batch or real-time targets with minimal boilerplate.
  • Build our real-time ML inference platform. Stand up and scale low-latency model serving.
  • Expand batch ML inference. Improve scheduling, parallelism, cost controls, observability, and failure/rollback for large-scale batch scoring and post-processing.
  • Own and expand the feature store. Design offline/online feature definitions, high read/write throughput, and consistent offline/online semantics.
  • Platform reliability and observability. Instrument training/inference for latency, throughput, accuracy, drift, data quality, and cost; build alerting and dashboards; drive incident response and postmortems.
  • Underwriting infrastructure partnership. Support production batch and real-time underwriting systems in collaboration with Data Science; collaborate on model interfaces, SLAs, safety checks, and product integrations.

What We Are Looking For
  • 5+ years of software engineering experience, including experience on ML platform/MLOps systems (training, deployment, and/or feature pipelines).
  • Strong Python; solid software design and testing fundamentals. Proficiency with SQL; hands-on Spark/PySpark experience.
  • Knowledge of ML fundamentals-probability & statistics, supervised vs. unsupervised learning, bias/variance & regularization, feature engineering, model evaluation metrics, validation strategies, and production concerns like drift, stability, and monitoring.
  • Expertise with modern data/ML stacks-AWS, Databricks (workflows, lakehouse, MLflow/registry, Model Serving), and Airflow (or equivalent orchestration).
  • Experience building real-time systems (service design, caching, rate limiting, backpressure) and batch pipelines at scale.
  • Practical knowledge of feature-store concepts (offline/online stores, backfills, point-in-time correctness), model registries, experiment tracking, and evaluation frameworks.
  • Strong problem-solving skills and a proactive attitude toward ownership and platform health.
  • Excellent communication and collaboration skills, especially in cross-functional settings.

Bonus Points
  • Databricks experience (MLflow, Model Serving).
  • Experience with feature stores (e.g., Tecton, Feast) and streaming (Kafka/Kinesis).
  • Experience with fintech, risk, or underwriting systems; familiarity with model safety checks, rejection/override flows, and auditability.
  • Background with A/B testing platforms, shadow/canary deployments, and automated rollback.
  • Experience with low-latency inference systems.

What We Offer
  • Salary Range: $220k - $265k
  • Equity grant
  • Medical, dental & vision insurance
  • Work from home flexibility
  • Unlimited PTO
  • Commuter benefits
  • Free lunches
  • Paid parental leave
  • 401(k)
  • Employee assistance program

If you require reasonable accommodation in completing this application, interviewing, completing any pre-employment testing, or otherwise participating in the employee selection process, please contact us.

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