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Selected role

ML Engineer

Elevate North Carolina, United States

$401k Senior Full-time

About Elevate
Elevate is a full-service consulting firm that inspires high-performing organizations to find their limits and push past them. With expertise in brand consulting, sales strategy, data-driven insights, and talent optimization, Elevate gives its clients a competitive edge in the fight for people’s precious time and attention. Established in 2018, Elevate set out to help sports teams and leagues spark innovation and drive performance. In the years since, the world of sports has transformed, today standing at the convergence of media, entertainment, and consumer brands, with Elevate supporting some of the world’s most ambitious businesses across these sectors. Elevate’s proprietary technology, data sources, and software products combined with our thoughtful insights, and people-centric approach give clients a 360-degree view of their customers, underpinning intelligent decision-making on marketing spend, growth strategy, and more.

Our team of 400+ employees spans the globe with in 20 locations worldwide. We value recruiting diverse individuals to our team to bring new perspectives to our company and look forward to learning more about you in the recruitment process. To learn more and see what we’ve been up to, follow Elevate on X, LinkedIn, and Instagram.

Where you come in
Elevate is embarking on an exciting transformation journey from a consulting company to a product-led organization where our technology will become a primary revenue driver. Join our rapidly growing engineering team that's setting the foundation for this transformation.

You'll collaborate with talented engineers, data scientists, and product leaders to build intelligent systems that enhance our product platforms. You'll develop ML models for dynamic pricing, demand forecasting, recommendation systems, and predictive analytics that enable clients to maximize revenue and optimize business outcomes. Your work will directly impact how we price products, recommend content, and optimize operations across our platforms.

What You'll Bring

ML Engineering Expertise: 3+ years of experience building and deploying machine learning systems in production environments
Python & ML Frameworks: Strong Python skills with experience in PyTorch, TensorFlow, scikit-learn, or similar ML frameworks
Model Deployment: Experience deploying ML models to production, including MLOps practices, model versioning, and A/B testing
Data Pipeline Experience: Strong background building data processing pipelines for training and inference
Cloud ML Platforms: Experience with AWS SageMaker, GCP AI Platform, Azure ML, or similar cloud ML services
Product Engineering Mindset: Understanding that technology exists to solve customer problems and create business value
Problem-Solving Approach: You start with understanding the problem deeply before jumping to solutions
Experimentation Mindset: You value learning through rapid experimentation and embrace a "progress over perfection" approach
Outcome Orientation: You measure success by business impact and customer satisfaction, not just by model accuracy metrics
Communication Skills: Ability to explain ML capabilities and limitations to both technical and non-technical stakeholders
Agency Experience: Experience working effectively with development agency partners is a plus
Domain Experience: Background in pricing systems, recommendation engines, or transactional platforms is highly valuable

How You'll Make An Impact

Build Pricing Models: Develop and deploy ML models for dynamic pricing that optimize revenue and business outcomes
Create Recommendation Systems: Build recommendation engines that suggest relevant content and products to users
Enable Demand Forecasting: Develop predictive models that forecast demand to optimize inventory and pricing strategies
Integrate ML into Products: Seamlessly embed ML models into our product backend services and APIs
Optimize for Scale: Build systems that can handle real-time inference at scale while maintaining model performance
Establish MLOps Practices: Create pipelines for model training, deployment, monitoring, and iteration
Solve Real Business Problems: Work directly with product managers and stakeholders to understand problems and validate ML solutions
Collaborate Across Teams: Partner with engineers, data scientists, and product teams to deliver cohesive ML-powered solutions

*Your Journey: First 90 Days

First 30 Days**

Deep dive into our existing platform architecture, data infrastructure, and business requirements
Understand current pricing strategies, recommendation approaches, and optimization challenges
Build relationships with your engineering teammates, data scientists, key stakeholders, and agency partners
Partner with the team to develop your personal roadmap for impact

Days 31-60

Implement your first ML model for a core use case (e.g., pricing or recommendations)
Design and run experiments to validate model performance and business impact
Begin establishing patterns for ML development, deployment, and monitoring

Days 61-90

Deploy ML models into production and monitor their performance
Lead technical planning for scaling ML capabilities across the platform
Contribute to roadmap for next-generation ML features and capabilities

Why This Role Matters Now

Growing Team: Join a talented and expanding engineering team that's building the foundation for Elevate's product-led future
Product-Led Transformation: Drive the shift to a product-led organization following the playbook of companies like Spotify, Airbnb, and Stripe
Learning Culture: Grow alongside passionate engineers in an environment that values continuous learning and knowledge sharing
Significant Impact: Your ML models will directly enable products that drive millions in revenue for our clients
Autonomy and Ownership: Lead with significant autonomy while owning outcomes, not just outputs

The Technology You'll Work With

Our ML stack includes:
ML Frameworks: PyTorch, TensorFlow, scikit-learn, XGBoost
Data Infrastructure: AWS (Redshift, Glue, S3, Lambda, SageMaker)
Model Deployment: AWS SageMaker, Lambda, ECS
Data Processing: Pandas, NumPy, Spark
Development Practices: MLOps pipelines, model versioning, A/B testing frameworks, CI/CD

Our Product Engineering Principles

Customer Obsession: We start with the customer and work backward. We don't build features; we solve customer and business problems.
Ownership: Teams own outcomes, not just outputs. Success means business impact and customer delight, not shipping on schedule.
Simplicity: We choose architectural and product simplicity over complexity. Complex solutions are harder to maintain, evolve, and explain.
Data-Driven Decisions: We measure what matters and use data to guide our product development and business decisions.
Rapid Learning: We implement quick feedback loops, focus on learning through experimentation, and value progress over perfection.
Transparency: We invite visibility and are transparent with where we're spending our time.

We're looking for engineers who want to do the best work of their careers while transforming how the sports and entertainment industry operates. At Elevate, you'll have the freedom to solve meaningful problems, the support to grow as a leader, and the satisfaction of seeing your work impact millions of fans. If you're ready to help shape our product-led future, we'd love to connect.

Position And Benefits Details

Full Time, Exempt
Medical, Dental, Vision, Life, Short-Term & Long-Term Disability Insurance + FSA, HSA, and more
401k Employer Match after meeting eligibility requirements
14 Paid Holidays
Unlimited PTO
Paid Parental Leave

Working Conditions
*Travel Requirements*

Occasional travel may be required

Physical Demands

Extensive work in front of a screen

Work Environment

This role is remote, with the potential for a hybrid work arrangement in the following cities: New York, NY; Santa Clara, CA; Charlotte, NC; Salt Lake City, UT; or Nashville, TN.

This position is open to all qualified candidates. If you need assistance or an accommodation due to a disability in connection with the application process, you may contact us at
[email protected]

We are proud to be an equal opportunity/veterans/disabled/ LGBT employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. All employment is decided based on qualifications, merit, and business need, without regard to race, color, religion, gender, sexual orientation, national origin, disability status, protected veteran status, genetic information, or any other characteristic protected by applicable law.

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