Senior Machine Learning Engineer
Chartbeat
Want to use your machine learning skills to understand and influence digital content strategies for many of the world’s largest media companies? Love to dig into mountains of data on the latest trends in social video viewing behavior? A machine learning role at Chartbeat provides a unique opportunity to help media brands make sense of the data they capture about viewers of digital content on their owned and operated site, and combine that with insights gleaned from social audiences to drive informed decisions that grow their reach and revenue.
Summary of the Role
As a Senior Machine Learning Engineer at Chartbeat, you will play a lead role in the development of new machine learning-based product capabilities, working as part of a diverse team of other Machine Learning Engineers, Data Scientists, and Data Analysts and collaborating cross-functionally with Engineering and Product. You will also take responsibility for the ongoing operations of our machine learning tools and infrastructure, advocating for and supporting the tooling and infrastructure needs of the team. You will participate and/or lead discussions on machine learning approaches appropriate for solving Chartbeat’s business problems, contribute and review code, and work with Chartbeat’s most experienced engineers to architect and build large-scale ML systems that can support required training and serving workloads.
The Senior Machine Learning Engineer will join the Data Science team, managed by Bonnie Ray, VP Data. The Data Science team operates as part of the larger Data team, responsible for curating, enriching, and modeling Chartbeat’s data to facilitate product discovery, ML-based product differentiation, and internal business decision making.
Key Duties & Responsibilities
- Lead development of new machine learning based product capabilities, such as metadata creation for news articles, conversion propensity modeling, or automated generation of business insights.
- Build and maintain tooling and infrastructure to allow data scientists to focus on experimentation while empowering self-service workflows to deploy and serve models reliably and consistently.
- Support life cycle management of deployed machine learning models (e.g., new releases, change management, model monitoring and troubleshooting).
- Effectively collaborate with other data scientists, engineers, and product managers to deliver new product capabilities with clear business impact
- Mentor more junior data scientists and machine learning engineers to aid development of clean, reproducible, and highly performant machine learning systems
- Build robust, scalable, high performance prediction, optimization and recommendation ML solutions based on massive structured and unstructured data from various sources
- Provide innovative thinking and technical expertise to expand Chartbeat’s capabilities around natural language processing and generative AI
Minimum Qualifications
- 5+ years working as a practicing data scientist or machine learning engineer in industry, preferably for a B2B SaaS provider
- Experience developing, testing, and deploying Python-based machine learning algorithms in a production environment
- Experience implementing and working with commonly used platforms for managing ML workflows, such as MLflow, comet.ml, AWS Sagemaker, or similar
- Solid theoretical knowledge of statistical and machine learning algorithms, as evidenced by an undergraduate or graduate degree in a mathematics, computer science, or engineering-related discipline
- Proficiency with advanced SQL querying and knowledge of common data warehouse environments, such as Snowflake, Databricks, or similar
- Experience with Kubernetes, Docker or any other infrastructure or containerization management/automation platform.
- Excellent communication and collaboration skills, with the ability to effectively communicate technical concepts to both technical and non-technical stakeholders
- A passion for understanding behavioral data
Exceptional Candidates will have:
- Experience extracting insights from large text corpora using modern techniques
- Prior experience in the domain of media and content analytics
- Experience building and managing data pipelines
- Active presence in the DS/ML community, as evidenced by workshop or conference presentations, contributions to data science open source projects, involvement in pro bono data science initiatives, etc.
Compensation and Benefits
We are proud to offer our team members a competitive compensation plan that includes:
- Comprehensive Health, Dental, and Vision Insurance
- 401K with company match (100% of the first 3% and 50% of the next 2%)
- Fully Paid Parental Leave - 18 weeks for birthing parents, 12 weeks for non-birthing parents
- $100/month phone and internet stipend
- $50/month book and wellness reimbursement
- $250/year lifelong learning and development reimbursement
- $100/month coworking space reimbursement
- $300 stipend for home office setup
- Flexible work hours
- Unlimited PTO
- 11 paid holidays and December holiday closure
- Company-wide outings
- Hackweeks
The pay range for this position is: $150,000 - $200,000 per year. Please note that the foregoing compensation information is a good-faith assessment associated with this position only and is provided pursuant to applicable law.
