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Temporary Machine Learning Startup Jobs (NOW HIRING)

HADRIAN

Machine Learning Engineer

Los Angeles, CA

$160K - $250K/yr

As a Senior Machine Learning Engineer, you will play a key role in designing, building, and scaling ... Prior experience working in a startup environment Compensation For this role, the target salary ...

Scowtt Inc

Machine Learning Engineer I

Seattle, WA

$100K - $150K/yr

About Scowtt Scowtt is an early-stage startup transforming the way businesses convert leads into ... About the Role We are looking for a motivated, entry-level Machine Learning Engineer to help build ...

Scowtt Inc

Machine Learning Engineer I

Seattle, WA · On-site

$100K - $150K/yr

About Scowtt Scowtt is an early-stage startup transforming the way businesses convert leads into ... About the Role We are looking for a motivated, entry-level Machine Learning Engineer to help build ...

Swish Analytics

Machine Learning Engineer

San Francisco, CA · On-site +1

$160K/yr

Swish Analytics is a sports analytics, betting and fantasy startup building the next generation of ... The Data Science team is hiring an experienced Machine Learning Engineer with a background building ...

Ema

Software Engineer, Machine Learning

San Francisco, CA · On-site

$135K - $200K/yr

Most importantly, you are excited to be part of a mission-oriented high-growth startup that can create a lasting impact. You Will * Conceptualize, develop, and deploy machine learning models that ...

Ema

Software Engineer, Machine Learning

Bodega Bay, CA · On-site

$135K - $200K/yr

Most importantly, you are excited to be part of a mission-oriented high-growth startup that can create a lasting impact. You Will * Conceptualize, develop, and deploy machine learning models that ...

Keebo

Senior Machine Learning Engineer

$125.40K - $165.30K/yr

Keebo is a venture-backed startup that offers a turnkey cloud-based Data Learning platform for ... Built on state-of-the-art in machine learning and artificial intelligence, and over 15 years of ...

Extend

Manager, Machine Learning

$180K - $210K/yr

Required: * 6+ years of work experience building and deploying machine learning systems into ... Stock in an early-stage startup growing quickly. * Generous, flexible paid time off policy ...

Kikoff

Senior Machine Learning Engineer

San Francisco, CA · On-site

$123.10K - $169.10K/yr

This is a consumer fintech startup, and you will be working with serial entrepreneurs who have ... We are seeking a Senior Machine Learning Engineer to join our team. This role will focus on ...

SmarterDx

Staff Software Engineer, Machine Learning

$260K/yr

Nice To Haves * You're a former startup founder, or have been the first engineering hire at a ... Experience with end-to-end machine learning project lifecycle, from data collection and model ...

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How much do temporary machine learning startup jobs pay per year?

As of May 31, 2026, the average yearly pay for temporary machine learning startup in the United States is $42,584.00, according to ZipRecruiter salary data. Most workers in this role earn between $32,500.00 and $46,000.00 per year, depending on experience, location, and employer.
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Machine Learning Infrastructure Engineer

UniversalAGI

San Francisco, CA • On-site

$126.70K - $166.10K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 2 days ago

Job description

San Francisco | Work Directly with CEO & founding team | Report to CEO | OpenAI for Physics | 5 Days Onsite
Machine Learning Infrastructure Engineer
Location: Onsite in San Francisco
Compensation: Competitive Salary + Equity
Who We Are
UniversalAGI is building OpenAI for Physics. AI startup based in San Francisco and backed by Elad Gil (#1 Solo VC), Eric Schmidt (former Google CEO), Prith Banerjee (ANSYS CTO), Ion Stoica (Databricks Founder), Jared Kushner (former Senior Advisor to the President), David Patterson (Turing Award Winner), and Luis Videgaray (former Foreign and Finance Minister of Mexico). We're building foundation AI models for physics that enable end-to-end industrial automation from initial design through optimization, validation, and production. We're building a high-velocity team of relentless researchers and engineers that will define the next generation of AI for industrial engineering. If you're passionate about AI, physics, or the future of industrial innovation, we want to hear from you.
About the Role
UniversalAGI is hiring an Infrastructure Engineerto build and own the execution platform powering our research and customer deployments: data generation + simulation orchestration + training/fine-tuning infrastructure + benchmarking pipelines + production deployments in customer environments.
You'll work closely with the CEO and founding team to turn research into repeatable, scalable, reliable systems - internally and in customer infrastructure. This is a "ship outcomes" role: your work directly determines how fast we can iterate, how reproducible our results are, and how reliably we deliver in production.
What You'll Do
Build the foundation platform (internal)
  • Build and operate scalable infrastructure for data generation and simulation workflows (job orchestration, scheduling, queues, retries, observability).
  • Build reproducible pipelines for training/fine-tuning and benchmarking (artifact/version management, experiment tracking, dataset lineage).
  • Own cost/performance tradeoffs across compute, storage, networking, and runtime efficiency.
Deploy to customers (external)
  • Lead deployments of our stack into customer cloud/on-prem environments, including secure networking, permissions, and data movement.
  • Build robust deployment patterns: environment provisioning, CI/CD, rollbacks, monitoring, and incident response.
  • Partner with customers to ensure reliability and repeatability under real-world constraints (security, compliance, infra limits, data governance).

Qualifications
  • Strong software engineering skills (clean code, debugging, reliability, reproducibility).
  • Hands-on experience building/operating infrastructure for ML/compute-heavy workflows: pipelines, job orchestration, GPU compute, storage, CI/CD, monitoring.
  • Olympic athlete mindset: You have high standards for yourself and are obsessed with measurable improvement on the metrics you are delivering to customers.
  • Resourcefulness: you know when to do the "quick & correct" fix vs. when to invest in a robust solution, and you can justify the tradeoff with impact/
  • Ownership: Comfortable owning work end-to-end and being accountable for measurable outcomes.

Bonus Qualifications
  • Experience with workflow orchestration (e.g., Ray, Kubernetes, Slurm).
  • Experience with GPU infrastructure and distributed training systems.
  • Experience building evaluation/benchmarking frameworks with strong reproducibility guarantees.
  • Experience deploying into regulated / security-sensitive environments (gov/defense/enterprise).
  • Experience with simulation/HPC pipelines (CFD, meshing, batch workloads) is a plus but not required.
  • Experience in an FDE-style / delivery execution role (or similar "ship results fast" environments).

Cultural Fit
  • Technical Respect: Ability to earn respect through hands-on technical contribution
  • Intensity: Thrives in our unusually intense culture - willing to grind when needed
  • Customer Obsession: Passionate about solving real customer problems, not just publishing papers
  • Deep Work: Values long, uninterrupted periods of focused work over meetings
  • High Availability: Ready to be deeply involved whenever critical issues arise
  • Communication: Can translate complex model decisions to customers and team
  • Growth Mindset: Embraces the compounding returns of intelligence and continuous learning
  • Startup Mindset: Comfortable with ambiguity, rapid change, and wearing multiple hats
  • Work Ethic: Willing to put in the extra hours when needed to hit critical milestones
  • Team Player: Collaborative approach with low ego and high accountability
  • Bias for Action: Ships experiments fast, learns from failures, and iterates quickly

What We Offer
  • Opportunity to define the future of physics AI from the ground up
  • Work on cutting-edge problems at the intersection of deep learning and physics simulation
  • Direct collaboration with the founder & CEO and ability to influence company strategy
  • Competitive compensation with significant equity upside
  • In-person first culture - 5 days a week in office with a team that values face-to-face collaboration
  • Access to world-class investors and advisors in the AI space

Benefits
We provide great benefits, including:
  • Competitive compensation and equity.
  • Competitive health, dental, vision benefits paid by the company.
  • 401(k) plan offering.
  • Flexible vacation.
  • Team Building & Fun Activities.
  • Great scope, ownership and impact.
  • AI tools stipend.
  • Monthly commute stipend.
  • Monthly wellness / fitness stipend.
  • Daily office lunch & dinner covered by the company.
  • Immigration support.

How We're Different
"The credit belongs to the man who is actually in the arena, whose face is marred by dust and sweat and blood; who strives valiantly; who errs, who comes short again and again... who at the best knows in the end the triumph of high achievement, and who at the worst, if he fails, at least fails while daring greatly." - Teddy Roosevelt
At our core, we believe in being "in the arena. " We are builders, problem solvers, and risk-takers who show up every day ready to put in the work: to sweat, to struggle, and to push past our limits. We know that real progress comes with missteps, iteration, and resilience. We embrace that journey fully knowing that daring greatly is the only way to create something truly meaningful.
If you're ready to train the models that will revolutionize physics simulation, push the boundaries of what AI can learn, and deliver real impact, UniversalAGI is the place for you.

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