Is the Machine Learning Engineer position at Camus fully remote?

Yes, this Machine Learning Engineer position at Camus is a remote position. The role is available for candidates in United States.

Is this a full-time or part-time Machine Learning Engineer role?

This is a full-time Machine Learning Engineer position at Camus.

What benefits does Camus offer for this position?

Camus offers the following benefits: 401k Matching.

What is the salary range for the Machine Learning Engineer position?

The salary range for this Machine Learning Engineer role is $180k - $230k.

How do I apply for the Machine Learning Engineer position at Camus?

You can apply for this Machine Learning Engineer position by clicking the "Apply Now" button on this page, which will take you to Camus's application portal.

Machine Learning Engineer at Camus

United States

$180k - $230k

Apply Now

Remote Opportunity

Machine Learning Engineer

Join Camus as a senior professional working remotely from United States. Explore the role, benefits, and apply in one place.

Machine Learning Engineer

Camus

Full Time

$180k - $230k

2 months ago

The Role We're looking for a Machine Learning Engineer to own and advance the forecasting and predictive modeling capabilities at the heart of the Camus platform.

United States

Senior

Machine Learning

Forecasting

Predictive Modeling

+5 more

Job Description

The Role

We're looking for a Machine Learning Engineer to own and advance the forecasting and predictive modeling capabilities at the heart of the Camus platform. This is an individual contributor role with real technical depth and product influence; you'll be responsible for the full lifecycle of ML model development, from exploratory analysis and model design through to production deployment and monitoring.

This is not a role where the problem statements are handed to you. You'll work directly with Camus’ teams and external stakeholders to understand their data, define the right questions, and translate messy real-world signals into reliable, production-grade data driven analytics. You'll bring that ground-truth perspective back into product decisions, and work closely within the Engineering team to integrate ML models into our planning and operational workflows.

The forecasting and predictive modeling problems we're solving often don't have off-the-shelf answers. We work as a tight, technical team that moves with urgency but builds with the discipline that production-grade software demands. If you want to do the most technically interesting ML work in the clean energy space while directly shaping how it becomes a product, this is the role.

What You'll Do

Design, train, and evaluate predictive ML models with a focus on forecasting and time-series applications
Conduct exploratory data analysis, feature engineering, and statistical modeling across large structured and unstructured datasets
Collaborate with Engineering to define ML infrastructure requirements, and deploy and integrate ML models into operational workflows and decision-support tools
Work cross-functionally with Camus teams to define problem statements and translate business objectives into ML solutions
Communicate model performance, uncertainty, and limitations clearly to both technical and non-technical audiences
Champion ML best practices around reproducibility, versioning, and testing

What You'll Bring

PhD with 3+ years of industry experience, Masters with 5+ years, or Bachelors with 8+ years in Machine Learning, Statistics, Computer Science, Applied Mathematics, or a related quantitative field
Demonstrated track record of delivering ML models into production environments
Experience with time-series forecasting methods — including classical approaches (e.g. ARIMA) and modern ML-based methods (e.g. gradient boosting or temporal neural networks)
Strong proficiency in Python and core ML/data science libraries (PyTorch, scikit-learn, statsmodels, pandas, etc.)
Experience with probabilistic forecasting, uncertainty quantification and backtesting
Ability to translate ambiguous business problems into well-scoped ML projects
Comfortable operating with autonomy in a small team, balancing speed of delivery with the engineering discipline that production-grade software demands.

Nice to Have

Experience in the energy sector — e.g. load forecasting, renewable generation prediction, price modeling or grid operations
Experience with MLOps tooling and infrastructure: cloud platforms, containerization, and model serving patterns
Experience with data pipeline tooling, e.g. Airflow, Spark, or Databricks
Able to leverage AI code development tools to accelerate development

What We Offer

Competitive base salary
Comprehensive benefits, including FSA and 401k for full time employees
Fully remote workplace with options for in office work in the Bay Area
Flexible PTO, which we encourage you to use!
A real impact on climate change - we’re building the world we want to live in and we want you to join us!

The expected base salary for this role is $180,000 - $230,000 annually, depending on experience, skills, and qualifications.

Benefits

401k Matching

Skills

Machine Learning

Forecasting

Predictive Modeling

Python

PyTorch

SciKit-Learn

statsmodels

Pandas

Ready to Apply?

Join Camus today

Salary Range

$180k - $230k

Posted 2 months ago

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