Senior Machine Learning Engineer

gobravvo; Seattle (WA); Remote; USD 150,000 - 210,000; Full time

Benefits offered by this job

Equity

Health insurance

Flexible PTO

Fully remote

Job summary

AZX seeks a Senior Machine Learning Engineer to shape core AI infrastructure for energy-focused client solutions. You will design, develop, and maintain scalable ML models and libraries, enabling reusable capabilities across client engagements and open-source projects.

This remote role partners with industry leaders to drive decarbonization and climate resilience. You will collaborate with cross-functional teams, contribute to energy system tools, and help build simulation engines for grid and

Qualifications

• 5+ years delivering applied ML solutions for real-world signals such as forecasting, disaggregation or detection
• Proficient in Python and systems language (ideally Rust) with robust libraries
• Strong numerical and scientific computing background; feature engineering from raw interval data
• Experience with time-series, forecasting, clustering libraries and SQL/Postgres or TimescaleDB

Responsibilities

• Develop and maintain reusable ML libraries for forecasting, disaggregation, demand response and asset health
• Design and implement validated libraries for reliability across client deployments
• Manage a high‑performance simulation engine with benchmark validation
• Develop grid‑data toolkits: codecs, synthetic scenario generators, verification utilities
• Build planning and dispatch support systems for demand-response programs
• Publish versioned software packages with documentation and benchmarks
• Establish feedback loops with client-facing teams to improve ML capabilities
• Collaborate with cross-functional teams and open-source initiatives in energy systems

Skills

Python

Rust

Time-series analysis

Forecasting

SQL/Postgres

Data engineering

Open-source

Education

Bachelor's degree in a relevant field

Master's degree (asset)

Tools

sktime

statsforecast

Job description

Senior Machine Learning Engineer - Summary

The Senior Machine Learning Engineer (ML Engineer) plays a crucial role in shaping the core AI infrastructure and tools that drive innovation and efficiency for utility‑focused client solutions at AZX. As a Senior Machine Learning Engineer, you will design, develop, and maintain robust machine learning models and underlying systems, ensuring scalable, reusable capabilities for client‑facing teams. This full‑time position is remote and offers the opportunity to collaborate with industry leaders while contributing to the open‑source community. If you are passionate about AI, clean energy, and sustainability, this role offers a dynamic environment to apply your technical expertise and make a significant impact. AZX is dedicated to accelerating positive change in critical sectors through advanced AI transformation, focusing on physics‑informed machine learning and enterprise‑scale solutions for climate, energy, and sustainability challenges. By joining our fast‑growing team, you will help build foundational tools used across diverse client engagements, from real‑time grid sensor data integration to sophisticated simulation engines for building energy analysis. This position also involves collaborating closely with internal teams and external users, ensuring the continuous improvement of our machine learning platforms based on real‑world feedback. Working with AZX provides the unique benefit of contributing to projects that have tangible impacts on decarbonization, climate risk assessment, and the evolution of energy systems. As a Senior Machine Learning Engineer, you will also find opportunities for professional growth, knowledge sharing, and long‑term career development—all within a fully remote, inclusive, and mission‑driven company culture.

Duties & Responsibilities

• Develop and maintain reusable utility‑focused machine learning libraries for forecasting, disaggregation, demand response, detection, and asset health assessment.
• Design and implement tested libraries with validation harnesses to ensure reliability and consistency across client deployments.
• Manage and optimize a high‑performance simulation engine, including validation against reference benchmarks and ensuring scalability for city‑scale building stock analysis.
• Develop and maintain grid‑data toolkits—protocol codecs, synthetic scenario generators, and verification utilities to support a broad range of energy and utility applications.
• Build and refine planning and dispatch support systems for demand‑response programs, emphasizing accuracy and reliability.
• Publish versioned software packages and provide comprehensive documentation, evaluation benchmarks, and performance evidence for internal and external users.
• Establish and maintain a feedback loop with client‑facing teams to iteratively improve machine learning capabilities based on field data and user experience.
• Collaborate with cross‑functional teams and contribute to open‑source initiatives related to energy systems and AI technologies.

Salary & Benefits

• Competitive salary and bonus eligibility aligned with experience and capabilities.
• Equity participation for long‑term alignment with company growth.
• Comprehensive health insurance, including coverage for dependents.
• Flexible paid time off to support work‑life balance.
• Fully remote work culture with periodic company summits for collaboration and team building.
• Opportunity to work with industry‑leading clients and contribute to impactful projects in energy, utilities, and sustainability sectors.

Qualifications & Requirements

• Minimum of 5 years of experience delivering applied machine learning solutions for real‑world signals such as forecasting, disaggregation, detection/classification on interval or sensor data, or survival/reliability modeling.
• Proficient in Python and experience with a systems language (ideally Rust); ability to build, test, and document robust libraries for broad engineering consumption.
• Strong background in numerical and scientific computing, including feature engineering from raw interval data and solver‑level computation.
• Experience with time‑series analysis, forecasting, clustering libraries (such as sktime, statsforecast), and working knowledge of SQL/Postgres or TimescaleDB‑class databases.
• Hands‑on approach to data engineering, including data sourcing, cleaning, joining, and profiling.
• Ability to quickly learn energy domain‑specific terminology and concepts as needed.
• Bachelor’s degree in a relevant field; a master’s degree is considered an asset.
• Comfort working in a fast‑paced, collaborative environment and engaging with open‑source communities.

Ideal Candidate Snapshot

• Self‑motivated, detail‑oriented professional with a passion for AI‑driven solutions in the energy and utilities sector.
• Proven track record of building and maintaining scalable, reliable machine learning tools and infrastructure.
• Comfortable collaborating remotely with distributed teams and external stakeholders.
• Adaptable and eager to learn new technologies, methodologies, and domain knowledge.
• Values inclusive, mission‑driven work environments focused on positive impact.

Other Relevant Information

This is a remote, full‑time opportunity with AZX, a company committed to diversity, equity, and inclusion in all hiring and workplace practices.

All candidates must be authorized to work in the United States; AZX is unable to sponsor employment visas at this time.

The hiring process includes a written take‑home assignment and a technical interview session to assess practical skills and alignment with the job requirements.

AZX encourages applications from candidates of all backgrounds, even if all requirements are not met.

AZX is an equal opportunity employer. We are committed to building a diverse and inclusive team and do not discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, disability, veteran status, or any other characteristic protected by applicable law.