H2Ok Innovations

About Us

At H2Ok Innovations, we're leading the charge in cleantech innovation, reshaping process industrials and manufacturing to drive operational efficiency and sustainability for our world’s most foundational industries. Powered by our H2Ok AI Co-pilot models and state-of-the-art sensors, our solutions optimize facility performance across various processes, including process manufacturing, production, water management, energy reduction, and waste minimization. Based at Greentown Labs, North America's premier cleantech innovation community, we're a woman-founded startup backed by renowned investors like Construct Capital, 2048 Ventures, and Flybridge Capital. Our groundbreaking technologies have earned accolades and adoption from industry giants like Unilever, The Coca-Cola Company, ABinBev, and Mitsubishi Electric. We're committed to unlocking untapped data for our customers, empowering them to gain a competitive edge and create Industry 4.0.

As our company scales, we're in search of an ML Scientist to join our expanding team. This full-time role is perfect for someone with a proven track record of designing, evaluating, and deploying cutting-edge machine learning models to production. This is a full-time role, perfect for someone with over 5 years of experience who thrives in a dynamic workplace and shares our passion for sustainability. The ideal candidate should be proficient in Python, knowledgeable in machine learning theory and frameworks, and familiar with building robust ML pipelines. Having a background in physics, chemistry, chemical engineering, process engineering, or similar is a plus.

What You Will Do

Build machine learning models for real-time processing and analysis of time-series data with high accuracy, low latency, and scalability.

Use knowledge of ML theory and practice to improve current state-of-the-art for models using time-series sensor data.

Develop generalizable, cutting-edge unsupervised models for time-series anomaly detection.

Apply critical thinking and first principles knowledge to develop optimization algorithms for black-box systems.

Collaborate with data scientists, software engineers, and other internal stakeholders to align ML models, ensuring they meet performance and reliability requirements.

Deploy ML models to Edge compute devices and monitor performance using best practices for MLOps.

About You

Highly knowledgeable in ML theory, architectures, and design.

Proficient in Python. Strong candidates may also be proficient in C++.

Experience using multiple ML frameworks (such as PyTorch, TensorFlow, Scikit-Learn, JAX) and numerical libraries (such as NumPy and Pandas). Knowledge of edge-specific frameworks (i.e. TensorFlow Lite) is a plus.

Experience building ML models with time-series or sequential data (such as NLP), especially for long time sequences and real-time processing scenarios. Experience working with sensor data is a plus.

Familiarity with reinforcement learning (RL), computational graphs, and/or graph neural networks is a plus.

Knowledgeable in techniques to optimize ML models for inference in compute-limited scenarios (i.e. model distillation, pruning, dimensionality reduction, feature selection, parallelization).

Familiar deploying models for fast, efficient inference on compute accelerators (TPUs or NPUs).Proficient in designing, implementing, and maintaining robust ML pipelines for end-to-end model lifecycle management. Experience benchmarking multiple models is a plus.

Familiar deploying models in containerized settings, such as Docker. Knowledge of Kubernetes and/or Docker Swarm is a plus. Familiar with SQL or similar database systems (such as MySQL, PostgreSQL, MongoDB).

Proficient in Git or other version control systems.

Familiar with cloud platforms such as AWS, Azure, or Google Cloud.

Experience working with LLMs/RAG is a plus, especially in building a company knowledgebase, chatbot, or for data analysis/summarization. Familiarity with Agile methodologies and experience in collaborative, cross-functional teams.

Analytical thinker with the ability to solve complex problems efficiently.

Excellent communication skills to articulate technical issues, solutions, and progress effectively.

Adaptability to learn new technologies and adapt to evolving project requirements.

Strong team player mindset, comfortable sharing knowledge and collaborating within a team environment.

Familiarity with Agile methodologies and experience in collaborative, cross-functional teams.

Analytical thinker with the ability to solve complex problems efficiently.

Meticulous attention to detail in writing clean, maintainable code and designing robust database architectures.

Excellent communication skills to articulate technical issues, solutions, and progress effectively.

Adaptability to learn new technologies and adapt to evolving project requirements.

Benefits

Direct impact on product and culture.

Comprehensive benefits package including Medical, Dental, Vision, Life Insurance, Disability, Transportation benefit, Health and Wellness benefit, and more.

401k plan with employer matching

Competitive salary and bonus opportunities.

Dynamic and inclusive work environment.

Opportunities for growth and professional development.

Access to Greentown Labs' extensive network of cleantech startups.

Machine Learning (ML) Scientist

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What You Will Do

About You

Benefits

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