Jobs Companies BetterHelp Machine Learning Engineer

Sobre este puesto de Machine Learning Engineer en BetterHelp

BetterHelp · Remoto · US - Remote

Who are we and why should you join us?

BetterHelp is on a mission to remove the traditional barriers to therapy and make mental health care more accessible to everyone. Founded in 2013, we are now the world’s largest online therapy service, providing affordable and convenient therapy across the globe. Our network of over 30,000 licensed therapists has helped millions of people take ownership of their mental health and change their lives forever. And we’re not stopping there – as the unmet need for mental health services continues to grow, BetterHelp is committed to being part of the solution.


As a Machine Learning at BetterHelp, you’ll join a diverse team of licensed clinicians, engineers, product pros, creatives, marketers, and business leaders who share a passion for expanding access to therapy. And as a mental health company, we take employee mental health just as seriously as we do our mission. We deeply invest in our team’s well-being and professional development, because we know that business and individual growth go hand-in-hand. At BetterHelp, you’ll carve your own path, make an immediate impact, and be challenged every day – with a supportive community behind you the whole way.

What are we looking for?

BetterHelp is looking for a Machine Learning Engineer to help build and scale the next generation of AI-powered experiences across our platform. This role will focus on Natural Language Processing (NLP), Large Language Models (LLMs), evaluation systems, and AI safety infrastructure.

We're looking for someone with a strong foundation in machine learning and NLP who is excited about building reliable, scalable AI systems in production. The ideal candidate has experience working with language models, evaluating model quality, implementing guardrails, and optimizing inference systems for real-world applications.

What will you do?

  • Develop and improve NLP systems and language model-powered experiences.
  • Fine-tune and optimize open-source and proprietary language models for domain-specific use cases.
  • Evaluate model performance and identify opportunities for quality improvements.
  • Design and implement evaluation frameworks to measure model quality, reliability, and business impact.
  • Build automated testing pipelines to identify regressions, quality drops, hallucinations, and failure modes.
  • Develop metrics and monitoring systems to continuously assess model performance in production.
  • Design and implement guardrails that improve model reliability, safety, and consistency.
  • Build systems to detect unsafe outputs, prompt injection attempts, abuse patterns, and fraud-related behaviors.
  • Partner with product and engineering teams to ensure AI systems behave predictably and responsibly.
  • Optimize inference performance through quantization, distillation, batching, and model serving improvements.
  • Deploy and maintain production-grade ML systems running on GPU infrastructure.
  • Improve latency, scalability, and operational efficiency of LLM-powered applications.
  • Partner closely with Product, Engineering, and Data Science teams to identify opportunities where AI can improve user experiences.
  • Translate business requirements into scalable ML solutions.
  • Communicate technical concepts clearly to both technical and non-technical stakeholders.

What will you NOT do?

  • You will NOT worry about "runway", "cash left", or "how much time we have until the next round". We have the startup DNA but we're fully backed and funded, all the way to success.
  • You will NOT be confined to your "job". You will get involved in product, marketing, business strategy, and almost everything we do.
  • You will NOT be bogged down by office politics, ego, or bad attitude. Only positive, pleasure-to-work-with people are allowed here!
  • You will NOT get yourself burned out. We work hard but we believe in maintaining a sustainable work/life balance. Really.

Can I work remotely?

Yes. We operate on PST and candidates in any time zone are welcome to apply. We ask employees to travel to our San Jose, CA office up to three times per year plus one company-wide offsite to collaborate in person and strengthen working relationships. Travel expenses are covered and reasonable accommodations are made for those under unique circumstances who cannot travel.

Requirements

  • Bachelor's degree in Computer Science, Artificial Intelligence, Machine Learning, Natural Language Processing, Statistics, Mathematics, Computational Linguistics, or a related quantitative field. Master's or PhD preferred.
  • 3+ years of industry experience building machine learning systems
  • Strong Python programming skills
  • Experience working with NLP and Large Language Models
  • Experience with PyTorch (preferred) or TensorFlow
  • Strong understanding of deep learning fundamentals, transformers, embeddings, and modern NLP architectures
  • Experience evaluating machine learning models and designing quality measurement frameworks
  • Experience fine-tuning language models for production use cases
  • Familiarity with model serving, inference optimization, and deployment workflows
  • Experience working with SQL and large-scale datasets
  • Excellent communication and collaboration skills

Benefits

  • Remote work with regular in-person bonding experiences sponsored by the company
  • Competitive compensation 
  • Holistic perks program (including free therapy, employee wellness, and more)
  • Excellent health, dental, and vision coverage
  • 401k benefits with employer matching contribution
  • The chance to build something that changes lives – and that people love
  • Any piece of hardware or software that will make you happy and productive
  • An awesome community of co-workers

The base salary range for this position is $150,000 - $180,000. In addition to the base salary, this position is eligible for a performance bonus and the extensive benefits listed here (subject to eligibility requirements): Teladoc Health Benefits 2026. Total compensation is based on several factors – including, but not limited to, type of position, location, education level, work experience, and certifications. This information is applicable to all full-time positions.

At BetterHelp we thrive on difference and individuality, and as part of the Teladoc Health family, we are proud to be an Equal Opportunity Employer. We never have and never will discriminate against any job candidate or employee due to age, race, ethnicity, religion, sex, color, national origin, gender, gender identity, sexual orientation, medical condition, marital status, parental status, disability, or Veteran status.

Notice to Candidates:
BetterHelp has been made aware of fraudulent job postings and unaffiliated third parties posing as our recruiting team – please know that we have no affiliation or connection to these situations. We only post open roles on our career page (betterhelp.com/careers) or reputable job boards like our official LinkedIn or Indeed pages, and all official BetterHelp recruitment emails will come from the domain @betterhelp.com. Our commitment is to ensure a safe and transparent hiring experience for all candidates.  We will never ask you for money, gift cards, or any form of payment during our hiring process, and we will never send money or checks to candidates. If you experience this, it is a scam.

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Cómo se compara este salario de ML Engineer

Este puesto paga $165,000/yrpor debajo de el rango típico para los puestos de ML Engineer.

$257,250 la mediana de $287,284 $375,009

Rango típico $261,775–$337,940/yr, a partir de 10 ofertas comparables de ML Engineer en JobsRadar (salario anualizado en USD). Ver datos salariales de ML Engineer →

Sobre BetterHelp

BetterHelp is the world’s largest online therapy service, facilitating millions of video sessions, voice calls, chats, and messages between therapists and members every month. Since 2013, our network of over 30,000 licensed, accredited, and board-certified therapists have helped more than 4,000,000 people face life’s challenges and improve their mental health.

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