Senior Machine Learning Engineer

Reposted Yesterday
Hiring Remotely in USA
Remote
145K-250K Annually
Senior level
Cloud • Software
The Role
Design, optimize, and deploy deep learning models for customer behavior prediction. Perform feature engineering, implement research-informed architectures, scale training pipelines, collaborate with client teams, document findings, and uphold engineering best practices.
Summary Generated by Built In
Who We Are

Every organization runs on intelligence: years of accumulated knowledge, decisions, and context. As AI takes on more of that work, companies face a choice: rent that intelligence from vendors who keep the data, the context, and the results, or own it.
OpenTeams exists to make ownership possible.
Founded by Travis Oliphant, creator of NumPy and SciPy, and built by people with deep roots across the open-source ecosystem, including NumPy, SciPy, PyTorch, and Jupyter, we help enterprises and governments build AI they control, govern, and evolve themselves.
If that sounds like your kind of work, we'd like to meet you.

Job Title: Senior Machine Learning Engineer

Location: Remote (U.S Strong Preference// W. Hemisphere Timezone required)

Work Authorization: Authorized to work where they live

Salary Range: 145,000 - 250,000 USD (dependent on experience level and location)

About the Role

We're seeking a Machine Learning Engineer to join our team supporting a strategic client engagement focused on deep learning model development for customer behavior prediction. You'll work alongside client data scientists and engineers to enhance and optimize deep-learning models that drive business decisions at scale.

This role involves hands-on work across the ML lifecycle—from feature engineering to model architecture improvements—within a collaborative, research-informed environment. You'll have the opportunity to implement techniques from cutting-edge academic research while contributing to production systems that directly impact business outcomes.

Key Responsibilities
  • Develop and refine features for deep learning models, working with large-scale customer and behavioral datasets
  • Implement model architecture changes informed by recent academic research (e.g., papers from NeurIPS and similar venues)
  • Collaborate with client teams to understand business context and translate requirements into technical solutions
  • Optimize model training pipelines for efficiency and scalability
  • Document approaches, findings, and technical decisions for knowledge sharing across teams
  • Participate in code reviews and contribute to engineering best practices
Required Skills & Experience
  • Strong proficiency with a deep learning framework (e.g. Pytorch, tensorflow)
  • Hands-on experience with feature engineering for predictive models
  • Solid foundation in machine learning fundamentals (supervised learning, neural network architectures, optimization)
  • Ability to read, understand, and implement techniques from ML research papers
  • Python proficiency in a data science/ML context
  • Comfortable working in ambiguous environments and adapting to unfamiliar tooling
Nice to Have
  • Experience with time-series or sequential modeling
  • MLOps experience (model deployment, monitoring, pipeline orchestration)
  • Familiarity with Google Cloud Platform or large-scale distributed training
  • Background in causal inference or attribution modeling
  • Experience working in consulting or client-facing technical role
Grow With Us

At OpenTeams, growth isn’t just about the company—it’s about you.
We believe the best careers are built at the edge of your potential. That is where new tools, ideas, and technologies change the world. Here, you’ll work alongside pioneers of AI, solving problems that matter: making AI more transparent, more ethical, and more empowering. As your skills grow, our career framework provides a pathway and recognition of that increased impact.

Opportunities aren’t limited by geography. You’ll collaborate with global experts, contribute to open source projects that power the world’s technology, and stretch your skills daily.  That global perspective and diversity makes our solution more universal and robust.  We are committed to continuing to celebrate diversity on our team.

Supported people are successful people.  We offer 100% employer paid medical premiums for employees and self-managed PTO with a minimum time off requirement, so that our teams are able to do their best work.
We invest  in curiosity, creativity, and ownership. That means you’ll be trusted to boldly innovate, supported to learn fast, and celebrated for successful collaboration.

Commitment to diversity, equity, inclusion, and belonging

OpenTeams understands that valuing diverse creative practices and forms of knowledge is crucial to and enriches the company’s core mission. We encourage applications from everyone, including members of all equity-seeking communities, such as (but certainly not limited to) women, racialized and Indigenous persons, disabled people, persons of all sexual orientations, gender identities and expressions.

We are an equal opportunity employer - all qualified applicants will receive equal consideration for recruitment, interviews, employment, training, compensation, promotion, and related activities. We do not discriminate based on race, religion, gender, gender identity, gender expression, color, national origin, pregnancy, ancestry, domestic partner status, disability, sexual orientation, age, genetic predisposition, medical condition, marital status, citizenship status, military or veteran status, or any other basis covered by applicable laws. OpenTeams will not tolerate discrimination or harassment based on these characteristics or any other unlawful behavior, conduct, or purpose.


Skills Required

  • Strong proficiency with a deep learning framework (e.g., PyTorch, TensorFlow)
  • Python proficiency in a data science/ML context
  • Hands-on experience with feature engineering for predictive models
  • Solid foundation in machine learning fundamentals (supervised learning, neural network architectures, optimization)
  • Ability to read, understand, and implement techniques from ML research papers
  • Comfortable working in ambiguous environments and adapting to unfamiliar tooling
  • Authorized to work where they live
  • Western Hemisphere timezone (W. Hemisphere) availability / U.S. strong preference
  • Experience with time-series or sequential modeling
  • MLOps experience (model deployment, monitoring, pipeline orchestration)
  • Familiarity with Google Cloud Platform or large-scale distributed training
  • Background in causal inference or attribution modeling
  • Experience working in consulting or client-facing technical roles
Am I A Good Fit?
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The Company
HQ: Austin, Texas
36 Employees
Year Founded: 2019

What We Do

OpenTeams is at the forefront of open source support, offering a wide range of practice areas led by a network of Open Source Architects. With over 680 open source technologies, our team provides comprehensive services including strategy and consulting, custom development, integration, migration, and 24/7 support. Our practice areas cover various domains, such as Machine Learning Operations, Cloud Optimization, Data Science and Engineering, SaaS and Cloud Applications, Artificial Intelligence and Machine Learning, PyTorch Hardware Optimization, PyTorch Artificial Intelligence System Building, and High-Performance Systems. Each solution is staffed by experienced professionals who assist businesses in addressing specific challenges and leveraging open source technologies to achieve their goals. OpenTeams is dedicated to helping clients build better software with reliable open source support.

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