AI/ML Engineer, 2027 New Grad

Brain Co is hiring an AI/ML Engineer, 2027 New Grad for a remote role open to applicants in United States. Level rates it ; you can apply on Brain Co.

Level's read on this job

On Level's scale, this machine learning engineer role is Builds AI ●●●●: the job is building AI systems.
This is listed as a remote role.
The posting mentions PyTorch, TensorFlow and JAX among its tools and skills.
Level classes it as a junior role.
Brain Co has 37 other open roles on Level.

AI in this role

pytorchtensorflowjax

rag

Our Mission

Rebuild how the world works, to make institutions work better for the people they serve.

About Brain Co.

Brain Co. builds AI-native operating systems for large, regulated institutions. Each system is built for a specific industry, powered by agents that push real workflows forward. Underneath it all is Atlas, our proprietary platform that keeps customers in control, secure by design, and never locked into one model.

Why Now

Brain Co. is entering its next phase of production deployments on a national scale with an elite team built from Palantir, Google, Meta, and Nvidia, and a growing footprint across government, insurance, health, and financial services.

Joining now means shaping both the company and a new category of applied AI. Every project here ships to production and is expected to create measurable customer value and impact.

You'll work alongside exceptional peers on some of the hardest problems in applied AI. It’s the kind of work you'll still be proud of in ten years from now.

At Brain Co., new-grad engineers contribute to real production systems and see their work deployed at global scale.

About the Role

As a Machine Learning Engineer at Brain Co., you will play a crucial role in deploying state-of-the-art models to automate various real world problems in sectors such as healthcare, government and energy. Part of the role will involve turning research breakthroughs into practical solutions for various nation states. This role is your opportunity to make a significant impact by making AI technology both accessible and influential.

What You’ll Work On

Innovate and Deploy: Design and deploy advanced LLM models to tackle real-world problems, particularly in automating complex, manual processes in a range of real-world verticals.
Optimize and Scale: Build scalable data pipelines, optimize models for performance and accuracy, and prepare them for production. Monitor and maintain deployed models to ensure they continue delivering value across various governments worldwide.
Make a Difference: Engage in projects including but not limited to optimizing the world's most advanced energy production systems, modernizing core government workflows, or improving patient outcomes in advanced public healthcare systems. Your work will directly impact how AI benefits individuals, businesses, and society at large.
Engage with Leaders: interact directly with government officials in various countries and apply the first of its kind AI solutions while working alongside experienced ex. Founders, AI researchers, and software engineers to understand complex business challenges and deliver AI-powered solutions. Join a dynamic team where ideas are exchanged freely and creativity flourishes. You will be able to wear many hats: software building, product management, sales, interpersonal skills.
Learn and Lead: Keep abreast of the latest developments in machine learning and AI. Participate in code reviews, share knowledge, and set an example with high-quality engineering practices.

You Might Be a Great Fit If You…

Expect to complete a bachelor’s degree in Computer Science, Engineering, Machine Learning, Data Science, or a related field in Spring 2027.
Have hands-on experience building GenAI-focused applications (e.g., agents, reasoning workflows, or RAG) and a solid understanding of how large language models are architected and operated.
Have personally implemented models in common ML frameworks such as PyTorch, Jax or TensorFlow.
Possess a strong foundation in data structures, algorithms, and software engineering principles.
Exhibit excellent problem-solving and analytical skills, with a proactive approach to challenges.
Can work collaboratively with cross-functional teams.
Thrive in fast-paced environments where priorities or deadlines may compete.
Are eager to own problems end-to-end and willing to acquire any necessary knowledge to get the job done.

Job Details & Benefits

Eligibility: Completing a bachelor’s degree in Spring 2027.
Competitive full-time compensation and benefits
Support and feedback from experienced platform engineers
Opportunity to work on real production systems used globally
Meaningful ownership from day one, with room to grow alongside the team
Daily lunches (if onsite)

How we rate this

AI/ML Engineer, 2027 New Grad at Brain Co rates 91 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Key facts

AI/ML Engineer, 2027 New Grad is an open job at Brain Co.
Level rates this role AI Level 4 of 4: Builds AI.
The role is based in San Francisco Bay Area and is marked remote.
The job was posted on October 1, 2026.
Seniority: junior.
Applications are handled by Brain Co. Apply on Brain Co

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

RAGPyTorchTensorFlowJAX

Also common in machine learning engineer jobs at this level

Python Deep learning AWS C++Spark Fine-tuning

Pay

Typical machine learning engineer job: $198k

This posting doesn't list pay. Use the typical machine learning engineer figure when pay comes up. See machine learning engineer jobs

Questions you could be asked

How would you design a retrieval step so the model answers from real data instead of guessing?
Walk me through how you've used PyTorch in your day-to-day work.
What are the limits of TensorFlow that you've run into, and how did you work around them?
What's a project where you used JAX hands-on?
How would you decide a model or AI system is ready to ship?

Adapt your resume

List these exact terms on your resume: RAG, PyTorch, TensorFlow, and JAX. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

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