Staff Machine Learning Engineer

No Longer Taking Applications

Job Description

At Teal, we’re setting out to level the playing field for job seekers by building a truly consumer-first platform that equips people with the tools, technology, and resources they need to feel empowered to achieve career growth on their terms. Our goal is to help people make confident career decisions from the day they start working to the day they retire—and that’s where you come in as our Staff Machine Learning Engineer. The role focuses on leading our efforts to level up and optimize the the capabilities of our our Generative AI that is already in production.

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As Teal’s Staff Machine Learning Engineer, you will be at the forefront of developing and deploying cutting-edge solutions that leverage AI agents and Large Language Models in order to help people take back control of their careers.

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Your work will involve a mix of developing machine learning services, managing Teal’s AI and ML product strategy, and optimizing our AI platform for performance, latency, scale, and cost. You will have ownership of your projects with minimal guidance, and help us continue to find a better way to make careers better for all of our users.

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Responsibilities

Design and implement secure, scalable, and high-performance pipelines managing the end-to-end lifecycle of ML models.
Offer strong technical leadership skills, consult with management, and educate and influence leadership on decisions affecting ML models and features based on them.
Own Teal’s AI and ML product strategy, influencing the team and demonstrating best practices.
Design and develop scalable AI and machine learning services for the engineering team, including setting up and maintaining robust APIs to integrate these services into production environments.
Integrate, test, and monitor ML model services across our product portfolio.

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Requirements

Must have worked on consumer facing applications and experience with experimenting and iterating on ideas that are best for users.
Ability to lead requirements collection, negotiate architectural decisions, and ensure platform scalability.
Drawn on a deep understanding of machine learning algorithms including large language models, and applying them effectively in ML projects.
Ability to design machine learning platforms for reuse and scalability, incorporating telemetry for complex failure mode analysis.
Possess a mastery of machine learning concepts like supervised and unsupervised learning, driving innovative solutions.
Experience with NLP and open source AI models.
Demonstrate a commitment to mentorship and elevating the capabilities of your team.
Knowledge of how to build quality controls around applications.
Experience with Vector databases for the implementation of RAG applications.
Experience with several ML and infrastructure systems in real world/production applications. The specific technology is less important to us than the experience with them.

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Nice-to-Haves

Experience with deploying agentic patterns to create autonomous systems that enhance the scalability and efficiency of machine learning applications.
Experience with Python frameworks such as Pandas, NumPy, PySpark for efficient ML operations.
Experience with frameworks such as Langchain, LangGraph and LlamaIndex.

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Skills & Tools You Will Use And Learn

Leveraging LLMs and SLMs in Production
Building ML systems using Python
Understanding our data sets and building value from them
Acquiring new data sets and constructing data pipelines for ML purposes
Building Agents and Agent-based systems

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Start Application

What Great Looks Like

At day 1:

Learn about our product’s LLM usage and review our existing prompts in Production

At 1 week:

You have a good idea of how we leverage LLMs
You have designed an improvement to a prompt and it pushed to production

At 1 month:

You’ve deployed your first full AI/ML feature.
You’ve associated this feature with a metric, and seen how your feature has moved the needle on this metric.

At 3 months:

You are fully fluent in our platform, showing us what is possible, what can be improved.
You are helping us plan our AI/ML roadmap

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Start Application

What We Offer

Salary: 190k-220k
Incentive Stock Options proportionate to salary
Fully remote work & remote office stipend (coworking, laptop, etc.)
Career development stipend
Unlimited vacation and sick days
Up to 12 weeks paid parental leave, earned 1 week for each month of tenure
80 - 100% coverage of health insurance (depending on chosen plan) & 401K Benefits with up to 4% company matching
As mentioned we are fully remote, however once per year we pay for the entire company to fly to the same city for a week of fun projects and general team building, think hackathons, boat rides and great food.
Guaranteed 1-month severance if Teal decides that things don’t work out. You are trusting us with your career, and we want you to know we take it seriously.

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About Teal & Our Hiring Practices

Who We Are

A small team of innovative, collaborative, and dedicated individuals passionate about helping people build meaningful careers. Our backgrounds range from Architecture to Digital Design and from Human Resources to Software Engineering. We are travelers, pet lovers, musicians, parents, scuba divers, podcasters, readers, gamers, croquet players, and puzzle masters. We focus on aligning intentions, resulting in fewer miscommunications, fewer meetings, and better outcomes. We adhere to a “what-by-when” mentality, which means the hours you keep are up to you, and we value your ability to set expectations and do your best to meet them.

Our Hiring Process

Apply

We read every application and make reply to everyone.
Please read the job description. We love when people strive but if you do not meet more than 50% of the requirements, we are less likely to respond.

Exploratory Interview

Goal: High-level qualifications & mutual fit
30-minute Zoom with the Director of Talent
We make sure to preserve 10 minutes for your questions.
We will provide the questions and guidance in advance.

Hiring Manager Interview

Goals: Deeper understanding of qualifications
45-minute Zoom with the Director of Data Engineering
This is a deeper discussion around our technical needs and understanding your knowledge and experience
We make sure to preserve 10 minutes for your questions.

Technical Interview

Goal: Assess your technical abilities and meet some of our engineering team
Review a take home assignment that will be given to you a couple days prior to the meeting
60 -minute zoom with our VP of Engineering and Staff Software Engineer
This is a practical exercise meant to simulate working with your team at Teal. Not an abstract puzzle or test set up to make people fail

Teal Values Interview

Goal: Meet more of the Team
60-minute Zoom with 2 Teal team members
We will provide the questions and guidance in advance.

Paid Work Trial

Goal: See you in action and let you work closely with your potential team, If you have reached this step, we are hoping that we have found out person.
You will be given a project to work on over a week and full access to any Teal resource and employee you need
You will be paid a rate in line with the salary for the role, we are not looking for free work
This is a mostly async process but you will be expected to join 1 all company meeting and participate in our company Slack.

Reference Interviews

We will ask for 2 references from your most recent managers that you are comfortable using as references.

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The anticipated application window is 21 days from the date job is posted, unless the number of applicants requires it to close sooner or later, or if the position is filled.

‍Commitment to Equal Employment Opportunity: (Come as you are. Feel welcome. Feel safe.) We are committed to safeguarding our workplace from all forms of discrimination and harassment on the basis of race, color, religion, sex, sexual orientation, gender identity or expression, age, national origin, disability, military status, or family status. This commitment extends to all aspects of the employment relationship, including recruiting, interviewing, selection, hiring, transfers, promotions, training, terminations, working conditions, compensation, and benefits.