My client is changing the way cities maintain their infrastructure by automating inspection processes and providing unmatched data insights. We are looking for a machine learning engineer to join our team who wants to work on our entire machine learning pipeline that helps my client deliver real-time insights to cities around the world and to ourselves. Preferred Qualifications<ul><li>A Master’s or PhD in a quantitative field or equivalent work experience</li><li>3+ years of experience building and deploying machine learning models and data products in production environments</li><li>Experience delivering data products based on tabular and time series datasets</li><li>Strong knowledge of machine learning techniques and tools, with experience in both classical methods and modern approaches (gradient boosted trees, neural networks)</li><li>Expert-level knowledge of statistics, both descriptive and inferential, with a strong foundation in Bayesian inference and probabilistic modeling techniques</li><li>Skilled practitioner of the Python data science stack (NumPy, SciPy, Pandas, Jupyter, etc.), along with strong SQL skills</li><li>Data visualization experience</li><li>Focus on creating robust data pipelines and ensuring accurate results are delivered</li><li>Strong verbal and written skills, with the ability to convey complex data models to non-technical audiences</li><li>Willingness to learn</li><li>Domain knowledge in infrastructure or asset management is a plus</li><li>Experience with cloud-based distributed training/inference management and orchestration</li><li>Familiarity with OLAP databases and real-time analytics</li></ul> About the JobWe are looking for a machine learning engineer to help us evolve our insights beyond single inspections to entire asset systems. Machine learning is a rapidly evolving field, and working in AI requires constant learning and exploration. We need someone ready to dive into the messy jungle of real-world data, with all its noise, inconsistencies, and variation. You'll be working at the forefront of machine learning to solve novel problems and create robust production systems.Working alongside the AI and Product teams, you will:<ul><li>Collaborate to develop requirements and understand the problem domain</li><li>Collect, clean, and pipeline data, creating and analyzing key features</li><li>Build and test machine learning models</li><li>Manage the ML pipeline</li><li>Participate in an agile development process</li><li>Have the opportunity to work on the entire technology stack</li></ul> Why Join?My client is applying AI to a massive infrastructure challenge. Most people aren't aware, but aging sewer infrastructure is leading to significant leaks and overflows, posing environmental and public health risks. We are revolutionizing this antiquated industry by automating the labor-intensive process of labeling cracks, roots, and grease in pipeline inspection videos. As a 5-year-old, Series B-funded startup with a large and growing client base, we are looking to expand our product offerings and continue their rapid growth. LocationThis is a hybrid position, with attendance expected in our Walnut Creek, CA office at least two days per week. Salary & Perks<ul><li>Tools you need to get the job done</li><li>Competitive salary and potential equity-based remuneration</li><li>Unlimited PTO</li><li>Budget for courses, books, and conferences – your development is important to us</li></ul> Keywords:AI, Machine Learning, Statistics, Time Series, Tabular Data, Python, SciPy, Data SciencePay range: $160,000 - $170,000 per year (Walnut Creek, CA)

Join Our Innovative Team!
We are transforming how cities manage their infrastructure through automation and unparalleled data insights. We are searching for a talented machine learning engineer to become part of our dynamic team, eager to work on a comprehensive machine learning pipeline that provides real-time insights to municipalities globally.
What We’re Looking For:
A Master's or PhD in a quantitative field, or equivalent experience
3+ years of hands-on experience building and deploying machine learning models and data products in production
Proficient in developing data products utilizing tabular and time series datasets
In-depth knowledge of machine learning methodologies, including both classical and modern techniques (e.g., gradient boosted trees, neural networks)
Expertise in statistics, with a solid grounding in Bayesian inference and probabilistic modeling
Proficient in the Python data science ecosystem (NumPy, SciPy, Pandas, Jupyter), with strong SQL abilities
Experience in data visualization
Strong focus on building robust data pipelines and delivering precise outcomes
Excellent communication skills to convey complex data models to non-technical stakeholders
A willingness to continuously learn and adapt
Knowledge in infrastructure or asset management is a plus
Experience with cloud-based distributed training and orchestration
Familiarity with OLAP databases and real-time analytics
Your Role:
As a crucial member of our team, your insights will help us advance our understanding from isolated inspections to full asset systems. The field of machine learning is continually evolving, and we seek someone ready to tackle the challenges of real-world data and its complexities.
You will work closely with the AI and Product teams to:
Collaborate in developing requirements and understanding problem domains
Collect, clean, and process data while creating and analyzing key features
Build and validate machine learning models
Manage the end-to-end ML pipeline
Engage in agile development processes
Contribute across the entire technology stack
Why You Should Join Us:
We are tackling significant infrastructure challenges through innovative AI solutions. Many people may not realize the impact of aging sewer systems, which can lead to dangerous leaks and environmental issues.
By modernizing the labor-intensive task of labeling cracks, roots, and grease in pipeline inspection videos, we are revolutionizing this outdated industry.
As a 5-year-old Series B-funded startup with a growing client base, we’re eager to expand our product offerings and further our rapid growth.
Location:  This is a hybrid role, requiring in-office attendance in Walnut Creek, CA at least two days a week.
Compensation & Benefits:
All the tools you'll need to succeed
Competitive salary with potential equity options
Unlimited PTO
Budget for professional development such as courses, books, and conferences
Keywords:  AI, Machine Learning, Statistics, Time Series, Tabular Data, Python, SciPy, Data Science
Salary:  $160,000 - $170,000 per year (Walnut Creek, CA)

My client  is changing the way cities maintain their infrastructure by automating inspection processes and providing unmatched data insights. We are looking for a machine learning engineer to join our team who wants to work on our entire machine learning pipeline that helps  my client  deliver real-time insights to cities around the world and to ourselves.
Preferred Qualifications
A Master’s or PhD in a quantitative field or equivalent work experience
3+ years of experience building and deploying machine learning models and data products in production environments
Experience delivering data products based on tabular and time series datasets
Strong knowledge of machine learning techniques and tools, with experience in both classical methods and modern approaches (gradient boosted trees, neural networks)
Expert-level knowledge of statistics, both descriptive and inferential, with a strong foundation in Bayesian inference and probabilistic modeling techniques
Skilled practitioner of the Python data science stack (NumPy, SciPy, Pandas, Jupyter, etc.), along with strong SQL skills
Data visualization experience
Focus on creating robust data pipelines and ensuring accurate results are delivered
Strong verbal and written skills, with the ability to convey complex data models to non-technical audiences
Willingness to learn
Domain knowledge in infrastructure or asset management is a plus
Experience with cloud-based distributed training/inference management and orchestration
Familiarity with OLAP databases and real-time analytics
About the Job
We are looking for a machine learning engineer to help us evolve our insights beyond single inspections to entire asset systems. Machine learning is a rapidly evolving field, and working in AI requires constant learning and exploration. We need someone ready to dive into the messy jungle of real-world data, with all its noise, inconsistencies, and variation. You'll be working at the forefront of machine learning to solve novel problems and create robust production systems.
Working alongside the AI and Product teams, you will:
Collaborate to develop requirements and understand the problem domain
Collect, clean, and pipeline data, creating and analyzing key features
Build and test machine learning models
Manage the ML pipeline
Participate in an agile development process
Have the opportunity to work on the entire technology stack
Why Join?
My client  is applying AI to a massive infrastructure challenge. Most people aren't aware, but aging sewer infrastructure is leading to significant leaks and overflows, posing environmental and public health risks.
We are revolutionizing this antiquated industry by automating the labor-intensive process of labeling cracks, roots, and grease in pipeline inspection videos.
As a 5-year-old, Series B-funded startup with a large and growing client base, we are looking to expand our product offerings and continue their rapid growth.
Location
This is a hybrid position, with attendance expected in our Walnut Creek, CA office at least two days per week.
Salary & Perks
Tools you need to get the job done
Competitive salary and potential equity-based remuneration
Unlimited PTO
Budget for courses, books, and conferences – your development is important to us
Keywords:
AI, Machine Learning, Statistics, Time Series, Tabular Data, Python, SciPy, Data Science
Pay range:  $160,000 - $170,000 per year (Walnut Creek, CA)

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