Mill
Mill is focused on reducing waste and its environmental impact by leveraging IoT data and AI at scale. This role leads a team to build data-driven solutions for consumer and business customers, guiding technical direction and people leadership.
Responsibilities
Provide technical leadership and architectural guidance across data engineering, algorithms, and AI projects. Analyze Mill's IoT data to identify trends, insights, and product opportunities. Develop data pipelines, predictive models, and business intelligence tools that empower our business customers. Establish standards for code quality, testing, and data governance. Champion a data-driven culture with metrics and evaluation frameworks to guide model selection and ensure rigorous testing. Lead the development and maintenance of internal data visualization infrastructure and collaborate with application teams to design customer-facing dashboards. Minimum Qualifications
7+ years of combined experience in software engineering, data science, machine learning, or data engineering, with at least 2 years in a lead or manager role guiding technical teams. Master’s, PhD, or equivalent experience in a quantitative field (e.g. Statistics, Computer Science, Data Science, Mathematics, Economics). A track record of data mining and data analysis, using data to solve business challenges at enterprise scale. Strong SQL knowledge and experience with relational and NoSQL databases. Hands-on experience with large-scale data platforms such as Snowflake, Redshift, BigQuery, or ClickHouse. Experience designing and building reports and custom visualization dashboards (e.g. Power BI, Tableau, Qlik, Plotly). Proven track record of delivering AI/ML solutions from prototype to production. Preferred Qualifications
Familiarity with AWS or other cloud providers, including ML/AI services like SageMaker or Bedrock. Python data science stack (Pandas, Dask, Numpy, Matplotlib, Seaborn, Jupyter, Visual Studio Code). Generative AI techniques and technologies (e.g., LLM inference, cross-modal vision-language models, prompt engineering, fine-tuning, agents, retrieval-augmented generation). Computer vision experience with CNN-based models using PyTorch and vision-language models. Experience with a wide range of ML algorithms and statistical techniques, including time-series analysis and A/B testing. Strong communication skills and ability to influence stakeholders at all levels. Passion for sustainability and solving real-world environmental challenges. Compensation
The estimated base salary range for this position is $220k to $250k, not including benefits or equity. Compensation is determined by multiple factors including skills, experience, and organizational needs. Additional Information
In-office expectation: role requires a minimum of 2 days per week in the office.
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Provide technical leadership and architectural guidance across data engineering, algorithms, and AI projects. Analyze Mill's IoT data to identify trends, insights, and product opportunities. Develop data pipelines, predictive models, and business intelligence tools that empower our business customers. Establish standards for code quality, testing, and data governance. Champion a data-driven culture with metrics and evaluation frameworks to guide model selection and ensure rigorous testing. Lead the development and maintenance of internal data visualization infrastructure and collaborate with application teams to design customer-facing dashboards. Minimum Qualifications
7+ years of combined experience in software engineering, data science, machine learning, or data engineering, with at least 2 years in a lead or manager role guiding technical teams. Master’s, PhD, or equivalent experience in a quantitative field (e.g. Statistics, Computer Science, Data Science, Mathematics, Economics). A track record of data mining and data analysis, using data to solve business challenges at enterprise scale. Strong SQL knowledge and experience with relational and NoSQL databases. Hands-on experience with large-scale data platforms such as Snowflake, Redshift, BigQuery, or ClickHouse. Experience designing and building reports and custom visualization dashboards (e.g. Power BI, Tableau, Qlik, Plotly). Proven track record of delivering AI/ML solutions from prototype to production. Preferred Qualifications
Familiarity with AWS or other cloud providers, including ML/AI services like SageMaker or Bedrock. Python data science stack (Pandas, Dask, Numpy, Matplotlib, Seaborn, Jupyter, Visual Studio Code). Generative AI techniques and technologies (e.g., LLM inference, cross-modal vision-language models, prompt engineering, fine-tuning, agents, retrieval-augmented generation). Computer vision experience with CNN-based models using PyTorch and vision-language models. Experience with a wide range of ML algorithms and statistical techniques, including time-series analysis and A/B testing. Strong communication skills and ability to influence stakeholders at all levels. Passion for sustainability and solving real-world environmental challenges. Compensation
The estimated base salary range for this position is $220k to $250k, not including benefits or equity. Compensation is determined by multiple factors including skills, experience, and organizational needs. Additional Information
In-office expectation: role requires a minimum of 2 days per week in the office.
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