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Senior Machine Learning Engineer
3 months ago
Cadent powers the evolution of TV brand advertising. We provide marketers, agencies, operators, and media owners with data-driven solutions for buying and selling TV advertising. By connecting brands with opportunities across national inventory sources—cable, broadcast, and digital media—our technology improves efficiencies and boosts the results of linear, addressable, and cross-screen campaigns. Right now, we are looking for a highly motivated Machine Learning Engineer who will be responsible for powering our Data Science department by scaling, deploying and managing advanced machine learning models. This will entail architecting and implementing big data solutions, data and model governance solutions, and implementing software development best practices. Machine Learning Engineers will collaborate directly with the Business, Product, Data Engineering, Data Science and QA team members to productize AI/ML research to drive business growth. Output from this role will be leveraged by business, engineers and by senior executives to define the future of Cadent.
What you will do:
- Scale, Deploy, Maintain, and Monitor Advanced Machine Learning Models:
Transform models provided by data scientists into production-ready products capable of running efficiently on full volume datasets. Leverage tools to automate retraining, deployment, and code quality checks. Establish, implement, and monitor business KPIs of model and infrastructure efficacy.
- Architect Multi-Cloud Big Data Solutions:
Design and develop infrastructure to process and store data at massive scale across GCP and AWS using IaC and SDKs. Analyze and optimize resources to adhere to governance, monitoring, and compliance policies. Work closely with DevOps, CloudOps, NetOps, SRE, and FinOps to implement solutions that are secure, reliable, and cost-effective.
- Design Data Governance and Model Governance Solutions:
Ensure transparency for operations and leadership regarding our data, processes, and models. Design and develop solutions to store, analyze, and report on key metadata for source datasets, derived datasets, and code.
- Drive Business Impact through Cross-Functional Collaboration:
Collaborate with various teams, including software engineers, product managers, data scientists, data engineers, and several operations teams to identify and prioritize machine learning opportunities. Quantify the impact of ML models and drive engineering decisions that maximize business value and operational efficiency.
- Set and Enforce Development Best Practices using TDD, V&V, and CI:
Collaborate with data scientists and engineers to establish standards and guidelines for quality, reliability, and performance of machine learning services. Stay updated on the latest advancements in software engineering, data engineering, ML engineering/ops, and cloud computing to ensure that Cadent keeps pace with evolving technologies. Provide guidance for Sr., mid-level, and associate MLEs on the team.
Cadent is an Equal Opportunity Employer and is committed to supporting all it’s employees when it comes to Inclusion & Diversity. Cadent’s policy is to provide equal opportunity for applicants & employees without regard to race, color, religion, creed, gender, gender identity or expression, sexual identity or orientation, age, national origin or ancestry, citizenship, disability or medical condition (including pregnancy, childbirth, or related medical condition), sexual and reproductive health decisions, genetic information, marital status (including domestic partnerships and civil unions), pregnancy, culture ancestry, familial or caregiver status, military status, veteran status, socioeconomic status, unemployment status, status as a victim of domestic violence or any other basis prohibited by law. and will not discriminate against the basis of disability. This commitment is honored when it comes to decisions on hiring, recruiting, training, promotions, compensations, benefits, transfers and terminations.
Cadent is seeking to actively engage with our employees from a wide variety of cultures and to connect with our clients differently. Our workforce has generational diversity that supports greater innovation when we maximize representation of all diversity. Our active employee resource groups promote engagement across all groups of individuals that are represented within the company and externally
