Raydar Logo

Raydar

Head of Machine Learning

Posted 51 Minutes Ago
Be an Early Applicant
Remote
Hiring Remotely in United States
230K-260K Annually
Expert/Leader
Remote
Hiring Remotely in United States
230K-260K Annually
Expert/Leader
Lead and grow a data science team building production machine learning models. Oversee the full model lifecycle, including data sourcing, feature engineering, training, deployment, and monitoring. Coach technical staff, manage planning and executive communication, investigate fraud patterns, improve model performance, and deliver dependable production code for real-time decisions. Present analyses that guide data strategy, product direction, operations, marketing, and sales.
The summary above was generated by AI

About the company

Our client is a fast-growing software company.

The role

Raydar is recruiting for this role on behalf of our client. Lead and expand a group of hands-on data scientists who develop and operate production machine learning models. Serve as a technical coach and as a partner to executives, product and engineering, setting priorities and delivering on tight schedules.

What you'll do

- Manage a small data science team and grow it over time as the work expands.

- Coach team members technically, reviewing details closely and giving clear guidance.

- Run planning, staffing and status updates with executives and cross-functional partners.

- Build commercial awareness and steer the team toward effective solutions under demanding deadlines.

- Own models across the whole lifecycle: data sourcing, feature design, labeling, training, experimentation, deployment and monitoring.

- Investigate emerging fraud patterns and shape new product offerings from what you learn.

- Improve model performance through iteration, new data sources and inventive feature work.

- Write dependable production code that supports real-time decisions for external partners.

- Produce and present analyses that guide data strategy, product direction, operational priorities, marketing and sales.


Requirements

What we're looking for

- Hands-on experience across the machine learning lifecycle, including feature work, training, deployment and monitoring.

- Several years of people management leading data science or ML teams that built products central to the business.

- Strong Python software engineering skills.

- Demonstrated success applying data science to difficult, visible business challenges, including growing a portfolio of models rather than a single one.

- Experience working in a fast-growing, early-stage company.

- A degree in a quantitative or technical field such as mathematics, statistics, computer science, physics or engineering.

- Comfort reporting progress and results to senior stakeholders.

- A stable work history with longer tenures at prior employers.

Bonus points

- Background in fraud, risk or financial services.

- A clear record of career growth.


Benefits

Compensation and benefits

- Base salary: USD 230,000 to 260,000 per year

- Equity

- Health insurance for you and your dependents

- Retirement plan with employer match

- Flexible paid time off

Location and work model

- Remote (US)

- Full-time

Similar Jobs

5 Days Ago
Remote
USA
230K-400K Annually
Senior level
230K-400K Annually
Senior level
Artificial Intelligence • Marketing Tech • Software • Analytics
Leads Hightouch’s machine learning organization, including product development, technical roadmapping, recruiting, reliability, and people management. The role focuses on personalization, product recommendations, probabilistic identity resolution, LLM-powered content generation, and scalable machine learning infrastructure for model training and inference.
Top Skills: Data WarehousesDatabasesLarge Language Models (Llms)Machine LearningMl InfrastructureModel InferenceModel Training
18 Days Ago
Remote
United States
292K-344K Annually
Senior level
292K-344K Annually
Senior level
Events • Music • Sports
Lead the development and production deployment of applied machine learning and LLM solutions across product, marketing, and operations. Own ranking, recommendation, filtering, personalization, experimentation, and model evaluation systems. Partner with business and technical teams to identify valuable use cases, establish modeling best practices, and ensure reliable production deployment. Manage and mentor applied ML practitioners while maintaining technical rigor, business alignment, and measurable customer and revenue impact.
Top Skills: EmbeddingsFine-TuningGradient BoostingLarge Language Models (Llms)Learning-To-RankMachine LearningMachine Learning Operations (Mlops)Neural NetworksPersonalizationPrompt EngineeringRecommendation SystemsRetrieval-Augmented Generation (Rag)
One Month Ago
Remote
United States
210K-260K Annually
Expert/Leader
210K-260K Annually
Expert/Leader
Fintech • Information Technology • Software
Leads an applied machine learning team and owns fraud detection and identity model strategy, development, deployment, monitoring, and iteration. Partners with Product, Engineering, Risk, and senior leadership to set priorities and deliver business impact. Provides technical mentorship, reviews code, guides modeling and architecture decisions, researches fraud patterns, develops ML capabilities, and shapes responsible AI use under data governance and security constraints.
Top Skills: AWSElasticsearchFlyteLarge Language ModelsMlflowNeo4JOpensearchPandasPostgresPython 3Scikit-LearnXgboost

What you need to know about the Austin Tech Scene

Austin has a diverse and thriving tech ecosystem thanks to home-grown companies like Dell and major campuses for IBM, AMD and Apple. The state’s flagship university, the University of Texas at Austin, is known for its engineering school, and the city is known for its annual South by Southwest tech and media conference. Austin’s tech scene spans many verticals, but it’s particularly known for hardware, including semiconductors, as well as AI, biotechnology and cloud computing. And its food and music scene, low taxes and favorable climate has made the city a destination for tech workers from across the country.

Key Facts About Austin Tech

  • Number of Tech Workers: 180,500; 13.7% of overall workforce (2024 CompTIA survey)
  • Major Tech Employers: Dell, IBM, AMD, Apple, Alphabet
  • Key Industries: Artificial intelligence, hardware, cloud computing, software, healthtech
  • Funding Landscape: $4.5 billion in VC funding in 2024 (Pitchbook)
  • Notable Investors: Live Oak Ventures, Austin Ventures, Hinge Capital, Gigafund, KdT Ventures, Next Coast Ventures, Silverton Partners
  • Research Centers and Universities: University of Texas, Southwestern University, Texas State University, Center for Complex Quantum Systems, Oden Institute for Computational Engineering and Sciences, Texas Advanced Computing Center

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account