ML Engineer

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.

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.

• 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, Tensor Flow, 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 Sage Maker, 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

• 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

• Deep dive into our existing platform architecture, data infrastructure, and business requirements
• Understand…