LLM Platform Engineer
WhatNotSalary not specified
Not SpecifiedCompensation
Mid-level (3 to 4 years)Experience Level
Full TimeJob Type
UnknownVisa
EdTechIndustries
Requirements
- 3–5 years building and shipping ML systems in production, with at least 6–12 months hands-on with LLM fine-tuning, prompt engineering, or RAG pipelines
- Fluency in Python for AI development and comfort working in Jupyter/IPython
- Solid understanding of modern ML tooling (e.g., PyTorch, TensorFlow, or JAX) and containerized/cloud deployment basics
- Clear, approachable communication with both technical peers and non-technical partners
- Bias toward action, curiosity, and comfort navigating ambiguity in a fast-moving startup environment
Responsibilities
- Prototype, fine-tune, and evaluate LLM-powered features—from conversational insights to practice-moment nudges—using Python and Jupyter notebooks
- Own the production lifecycle: data prep, experiment design, offline/online evaluation, and weekly pushes to prod alongside a tight squad of ML/Backend/Full Stack Engineers
- Collaborate daily with Product, Coaching Science, and Learning Design to turn behavior-change research into delightful user moments
- Contribute to technical design by shaping model architectures, retrieval strategies, and safety guards—while staying hands-on in code
- Measure what matters: define success metrics, implement A/B tests, and iterate quickly on real coach feedback
- Ship end-to-end improvements to products like FocusFrame, our AI copilot that helps coaches deliver higher-impact sessions in real time
Skills
Key technologies and capabilities for this role
Questions & Answers
Common questions about this position
What salary or compensation is offered for this Machine Learning Engineer role?
This information is not specified in the job description.
Is this Machine Learning Engineer position remote or does it require office work?
This information is not specified in the job description.
What are the core skills required for this Machine Learning Engineer role?
Candidates need 3–5 years building and shipping ML systems in production with 6–12 months hands-on with LLM fine-tuning, prompt engineering, or RAG pipelines, fluency in Python for AI development and Jupyter/IPython, solid understanding of modern ML tooling like PyTorch, TensorFlow, or JAX, and clear communication skills.
What is the company culture like at BetterUp for this role?
BetterUp offers a personal BetterUp Coach, the most curious teammates, and a mission-driven environment that emphasizes growth mindsets, bias toward action, curiosity, and comfort in ambiguity within a fast-moving startup.
What makes a strong candidate for this Machine Learning Engineer position?
Strong candidates have the core ML experience outlined, even if they don't hit every bullet, as BetterUp values growth mindsets and encourages applying anyway; bonus points for experience in coaching, learning-science, or related domains.
BetterUp
Digital coaching for leadership and employee development
About BetterUp
BetterUp provides professional coaching and personal development services primarily for businesses. Its main product is a digital platform that connects employees, managers, and executives with expert coaches. These coaches help individuals enhance their leadership skills, manage stress, and develop resilience and self-compassion. The platform uses insights and analytics to customize coaching programs to meet the specific needs of each organization, ensuring measurable improvements in employee performance and well-being. Unlike many competitors, BetterUp focuses on a subscription model, allowing companies to provide ongoing access to coaching resources for their employees. The goal of BetterUp is to significantly improve individual and team performance, resilience, and overall employee experience across various industries.
San Francisco, CaliforniaHeadquarters
2013Year Founded
$563.2MTotal Funding
SERIES_ECompany Stage
Data & Analytics, ConsultingIndustries
1,001-5,000Employees
Benefits
Medical, dental, & vision benefits
Flexible Time Off
Paid parental leave
Unlimited coaching
Wellness programs
Education & learning stipend
Volunteer days
Risks
Shift to in-office work increases burnout, potentially affecting BetterUp's client satisfaction.
High valuation post-pandemic may challenge BetterUp in maintaining growth and investor expectations.
Departure of key personnel like Katie Coupe could disrupt internal operations and talent management.
Differentiation
BetterUp is the inventor of virtual coaching, leading the mental health startup sector.
It offers the largest network of over 3,000 coaches in 46 languages worldwide.
BetterUp integrates AI technology to tailor coaching programs to individual and organizational needs.
Upsides
Growing demand for virtual coaching as hybrid work models become more prevalent.
Increased interest in workplace mental health solutions boosts BetterUp's market potential.
AI-driven analytics enhance personalized coaching, improving employee performance and well-being.
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