<div>Mill is all about answering a simple question: how can we prevent waste? Less waste can save time, money, energy, maybe even our planet. And there’s no better place to start than food. Food waste is one of the most solvable climate problems facing us today. Plus, our trash really stinks. It’s gross, heavy, and our least favorite chore. At Mill we are striving to build a better environment for all, as we take on climate and kitchen change.</div>Role Description:We’re seeking a Tech Lead Manager (TLM) to guide a small team focused on leveraging Mill’s extensive IoT data and AI capabilities for our consumer and business customers. You’ll set technical direction, roll up your sleeves to solve complex problems, and provide strong people leadership to help the team grow and thrive.You’ll partner closely with product and business stakeholders to translate strategic goals into practical data solutions, ensuring that our data pipelines, AI models, and analytics tools drive tangible value for customers and the planet.<h3>Responsibilities</h3><ul><li style="font-weight:400;">Provide technical leadership and architectural guidance across data engineering, algorithms, and AI projects.</li><li style="font-weight:400;">Analyze Mill's rich IoT data to identify trends, insights, and product opportunities.</li><li style="font-weight:400;">Drive the development of data pipelines, predictive models, and business intelligence tools that empower our business customers.</li><li style="font-weight:400;">Establish standards for code quality, testing, and data governance.</li><li style="font-weight:400;">Champion a data-driven culture by establishing robust metrics and evaluation frameworks to guide model selection and ensure rigorous testing.</li><li style="font-weight:400;">Lead the development and maintenance of our internal data visualization infrastructure, while collaborating with application teams to design customer-facing dashboards. </li></ul><h3>Minimum Qualifications</h3><ul><li style="font-weight:400;">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.</li><li style="font-weight:400;">Master’s, PhD, or equivalent experience in a quantitative field (e.g. Statistics, Computer Science, Data Science, Mathematics, Economics )</li><li style="font-weight:400;">A track record of data mining and data analysis, using data to solve business challenges at enterprise scale.</li><li style="font-weight:400;">Strong knowledge of SQL and experience with relational and NoSQL databases.</li><li style="font-weight:400;">Hands-on experience with large-scale data platforms such as SnowFlake, Redshift, BigQuery, or ClickHouse.</li><li style="font-weight:400;">Experience designing and building reports and custom visualization dashboards (e.g. Power BI, Tableau, Qlik, Plotly )</li><li style="font-weight:400;">Proven track record of delivering AI/ML solutions from prototype to production.</li></ul><h3>Preferred Qualifications</h3><ul><li style="font-weight:400;">Familiarity with AWS or other cloud providers, including ML/AI services like SageMaker or Bedrock.</li><li style="font-weight:400;">Python data science stack (Pandas/Dask/Numpy/Matplotlib/Seaborn/Jupyter/Visual Code)</li><li style="font-weight:400;">Generative AI techniques and technologies, such as small and large language model inference, cross-modal vision language models, prompt/context engineering, LORA fine-tuning, agents, RAG, MCP</li><li style="font-weight:400;">Computer vision experience, especially with models based on convolutional neural networks via the Pytorch ML framework and vision language models</li><li style="font-weight:400;">Practical experience with a wide range of machine learning algorithms (e.g. supervised, unsupervised, deep learning) and statistical techniques (e.g. regression analysis, hypothesis testing, A/B testing, time-series analysis).</li><li style="font-weight:400;">Strong communication skills and ability to influence stakeholders at all levels.</li><li style="font-weight:400;">Passion for sustainability and tackling real-world environmental challenges.</li></ul>The estimated base salary range for this position is $220k to $250k, which does not include the value of benefits or a potential equity grant. A wide range of factors are considered in making compensation decisions, including but not limited to skill sets, market conditions, experience and training, licensure and certifications, and business and organizational needs. At Mill, it is not typical for an individual to be hired at or near the top of the range for their role.

Trash stinks. Together, we can do better. Mill has created a new system to help you outsmart waste at home.

Data Tech Lead/Manager

<div>Mill is all about answering a simple question: how can we prevent waste? Less waste can save time, money, energy, maybe even our planet. And there’s no better place to start than food. Food waste is one of the most solvable climate problems facing us today. Plus, our trash really stinks. It’s gross, heavy, and our least favorite chore. At Mill we are striving to build a better environment for all, as we take on climate and kitchen change.</div>Role Description:We’re seeking a Tech Lead Manager (TLM) to guide a small team focused on leveraging Mill’s extensive IoT data and AI capabilities for our consumer and business customers. You’ll set technical direction, roll up your sleeves to solve complex problems, and provide strong people leadership to help the team grow and thrive.You’ll partner closely with product and business stakeholders to translate strategic goals into practical data solutions, ensuring that our data pipelines, AI models, and analytics tools drive tangible value for customers and the planet.<h3>Responsibilities</h3><ul><li>Provide technical leadership and architectural guidance across data engineering, algorithms, and AI projects.</li><li>Analyze Mill's rich IoT data to identify trends, insights, and product opportunities.</li><li>Drive the development of data pipelines, predictive models, and business intelligence tools that empower our business customers.</li><li>Establish standards for code quality, testing, and data governance.</li><li>Champion a data-driven culture by establishing robust metrics and evaluation frameworks to guide model selection and ensure rigorous testing.</li><li>Lead the development and maintenance of our internal data visualization infrastructure, while collaborating with application teams to design customer-facing dashboards. </li></ul><h3>Minimum Qualifications</h3><ul><li>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.</li><li>Master’s, PhD, or equivalent experience in a quantitative field (e.g. Statistics, Computer Science, Data Science, Mathematics, Economics )</li><li>A track record of data mining and data analysis, using data to solve business challenges at enterprise scale.</li><li>Strong knowledge of SQL and experience with relational and NoSQL databases.</li><li>Hands-on experience with large-scale data platforms such as SnowFlake, Redshift, BigQuery, or ClickHouse.</li><li>Experience designing and building reports and custom visualization dashboards (e.g. Power BI, Tableau, Qlik, Plotly )</li><li>Proven track record of delivering AI/ML solutions from prototype to production.</li></ul><h3>Preferred Qualifications</h3><ul><li>Familiarity with AWS or other cloud providers, including ML/AI services like SageMaker or Bedrock.</li><li>Python data science stack (Pandas/Dask/Numpy/Matplotlib/Seaborn/Jupyter/Visual Code)</li><li>Generative AI techniques and technologies, such as small and large language model inference, cross-modal vision language models, prompt/context engineering, LORA fine-tuning, agents, RAG, MCP</li><li>Computer vision experience, especially with models based on convolutional neural networks via the Pytorch ML framework and vision language models</li><li>Practical experience with a wide range of machine learning algorithms (e.g. supervised, unsupervised, deep learning) and statistical techniques (e.g. regression analysis, hypothesis testing, A/B testing, time-series analysis).</li><li>Strong communication skills and ability to influence stakeholders at all levels.</li><li>Passion for sustainability and tackling real-world environmental challenges.</li></ul>The estimated base salary range for this position is $220k to $250k, which does not include the value of benefits or a potential equity grant. A wide range of factors are considered in making compensation decisions, including but not limited to skill sets, market conditions, experience and training, licensure and certifications, and business and organizational needs. At Mill, it is not typical for an individual to be hired at or near the top of the range for their role.

Data Tech Lead/Manager

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Mill

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