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Senior Software Engineer - ML Infrastructure

Join Applied Intuition as a Senior Software Engineer to design and implement ML infrastructure for deep learning model training.

Location
Sunnyvale
Compensation
$215k–$285k/yr
Level
senior
Type
full time · On-site

Posted by employer 3 years ago

First seen on Joblaze 1 month ago

Last verified on the company career page 10 hours ago

Apply at Applied Intuition → Save job Scanned from appliedintuition.com

Requirements

Experience
3+ years
Education
Bachelor's degree

Not disclosed in this posting: visa sponsorship.

Benefits

401k Match Equity/Stock Options Paid Time Off Health Insurance

Joblaze summary

In this role, the Senior Software Engineer will focus on developing and implementing machine learning infrastructure, including building end-to-end ML pipelines and distributed cloud GPU training systems. Key skills include experience with full-stack machine learning challenges and familiarity with orchestration systems and ML frameworks like PyTorch or TensorFlow. This position is ideal for engineers with at least three years of experience who thrive in dynamic environments and enjoy tackling complex data problems. The team emphasizes collaboration and ownership, contributing to a culture of innovation at Applied Intuition.

Joblaze insights

  • Listed about a month ago — first seen on Joblaze September 3, 2026. Last confirmed on Applied Intuition's careers page October 29, 2026.
  • Salary band is above the typical range for AI/ML roles (median ~$190,000).
  • Starts above 60% of 62 comparable senior ai/ml roles in United States that list PyTorch we track (median $200,000 across 31 companies).
  • PyTorch appears in 18.8% of 549 comparable senior ai/ml roles in United States; Flyte appears in 0.2% of 549 comparable senior ai/ml roles in United States.

Quick facts

Is the Senior Software Engineer - ML Infrastructure role remote?
No — this is an on-site role in Sunnyvale.
What's the salary range?
Applied Intuition lists $215,000–$285,000 for this role.
How much experience is required?
At least 3 years of relevant experience for this Senior Software Engineer - ML Infrastructure role.
Where is the role based?
Applied Intuition is hiring for this position in Sunnyvale.
What's the tech stack?
Joblaze extracted these technologies from the posting: Airflow, Cloud, Deep Learning, Flyte, GPU, Machine Learning.
What seniority level is this role?
Applied Intuition targets senior candidates for this position.
Is this full-time or contract?
Full-time for this Senior Software Engineer - ML Infrastructure role at Applied Intuition.

From the original posting

About the role

We are looking for both infrastructure engineers with expertise in machine learning pipelines and ML engineers that want to work beyond modeling to join the Data & ML infra group. This role will work across the entire ML lifecycle (dataset generation, training frameworks, compute, evaluation, and deployment) and work directly with modeling teams. This team is a good fit if you are excited to work on broad, ambiguous problems and develop across the entire ML stack. At Applied Intuition, we encourage all engineers to take ownership over technical and product decisions, closely interact with external and internal users to collect feedback, and contribute to a thoughtful, dynamic team culture.

At Applied Intuition, you will:

  • Design and implement distributed cloud GPU training approaches for deep learning model training and evaluation

  • Build end-to-end machine learning pipelines and integrate them into core product workflows

  • Encourage change, especially in support of ML engineering best practices, and maintain a high standard of excellence

  • Collaborate with engineers across the entire company to solve complex data problems at scale

We're looking for someone who has:

  • A Bachelor's degree in Computer Science, Software Engineering, or equivalent

  • 3+ years of professional experience

  • Experience with building software components to address production, full-stack machine learning challenges. This is not purely a research problem

  • Opinions about building a company-wide platform for ML training, evaluation, and deployment

  • Knowledge of the open source landscape with judgment on when to choose open source versus build in-house

  • Excellent analytical and problem-solving skills

Nice to have:

  • Experience with developing, running, and managing orchestration systems like Airflow and Flyte that non engineers can use to build data pipelines.

  • Experience with ML modeling frameworks (PyTorch, Tensorflow, etc.), and model serving platforms  (TorchServe, TensorFlow Serving, NVIDIA Triton inference server, etc.)

Compensation at Applied Intuition for eligible roles includes base salary, equity, and benefits. Base salary is a single component of the total compensation package, which may also include equity in the form of options and/or restricted stock units, comprehensive health, dental, vision, life and disability insurance coverage, 401k retirement benefits with employer match, learning and wellness stipends, and paid time off. Note that benefits are subject to change and may vary based on jurisdiction of employment.

Applied Intuition pay ranges reflect the minimum and maximum intended target base salary for new hire salaries for the position. The actual base salary offered to a successful candidate will additionally be influenced by a variety of factors including experience, credentials & certifications, educational attainment, skill level requirements, interview performance, and the level and scope of the position.

Please reference the job posting’s subtitle for where this position will be located. For pay transparency purposes, the base salary range for this full-time position in the location listed is: $215,000 - $285,000 USD annually. 

Standard company text repeated across Applied Intuition's postings is omitted here.

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