Senior Applied ML Engineer

Senior Applied ML Engineer

• Pay Rate: $105.00 - $150.00/hour on W2 (Rate based on experience and interview performance)
• Location: Austin, TX or Atlanta, GA (Hybrid 2-3 days onsite)
• Contract Length: 1+ Years

Must be authorized to work in the United States. We are unable to sponsor or take over sponsorship of an employment visa at this time. This role is for direct W2, no C2C (corp to corp) available.

We are hiring a Senior Applied ML Engineer to join a product‑focused team building machine learning solutions  this role, you will contribute hands‑on engineering alongside mentorship and technical leadership. You are expected to work independently, influence technical decisions, and help shape the direction of ML systems across the product.

Senior engineers here are strong practitioners first. You will pair frequently with teammates, conduct code reviews, and set a high standard for quality and maintainability.

• Delivery & Execution (approx. 70% of time)
  • Build secure, reliable, and scalable ML features as a core member of a cross‑functional product team
  • Ensure quality and change control standards are consistently met; document systems and processes thoroughly
  • Write automation scripts for infrastructure, monitoring, and test coverage
  • Conduct stress and resilience testing to validate production readiness
  • Adapt off‑the‑shelf tools and platforms to fit evolving requirements
  • Create instrumentation including dashboards, alerts, and logging to enable proactive operations
• Continuous Learning (approx. 10% of time)
  • Participate in internal communities of practice and external learning forums
  • Independently research emerging ML techniques and tooling to inform team decisions
• Support & Enablement (approx. 20% of time)
  • Serve as a resource for partner teams and support functions
  • Monitor production systems and maintain awareness of Service Level Objectives
  • Regularly assess system capacity, prediction quality, and overall production health

• 2–4 years of relevant ML engineering experience
• Solid working knowledge of ML algorithms including clustering, forecasting, anomaly detection, and neural networks
• Practical experience with regression and foundational statistics
• Hands‑on use of ML frameworks and tooling:
  Jupyter Notebooks, Pandas, Sci Py, Scikit‑learn, Gensim, Tensor Flow, Py Torch
• Experience with a major cloud ML platform (e.g., Vertex AI, BigQueryML) and data engineering tools such as Big Query
• Proficiency in Python; experience with modern web frameworks (Node.js) and front‑end technologies (HTML, CSS, JavaScript, React, D3)
• Experience with GPU acceleration (CUDA, cuDNN)
• Strong SQL skills and experience with relational databases
• Proficiency with Git and CI/CD workflows
• Experience working in Linux/Unix environments
• Experience designing and consuming REST APIs
• Familiarity with production systems architecture including availability, failover, and security
• Familiarity with No
  
  SQL databases
• Familiarity with cloud automation patterns and managed ML services
• Familiarity with defensive coding and high‑availability patterns
• Exposure to A/B testing and scalable web service design
• Familiarity with advanced ML techniques such as NLP, convolutional neural networks, autoencoders, and embeddings

• Operates independently with minimal direction
• Navigates complexity and ambiguity with confidence
• Communicates clearly in technical and cross‑functional settings
• Brings innovative thinking to product and technical challenges
• Strong collaborator who actively supports team success
• Drives results consistently; holds self to a high standard