Staff ML Engineer

Raise; Austin (TX); On-site; USD 206,640 - 275,520; Full time

Job summary

Raise is seeking a Staff ML Engineer in Austin, TX to lead the technical strategy for machine learning systems. You will mentor engineers, drive initiatives, and ensure scalable ML solutions. This is a senior contributor role requiring collaboration with various teams to deliver impactful AI solutions.

With 3-6 years in the field and strong expertise in ML algorithms and advanced techniques, you will be integral to shaping project outcomes while adapting to evolving business needs.

Qualifications

• 3–6 years of relevant ML engineering experience.
• Deep expertise in ML algorithms such as clustering and neural networks.
• Strong command of Python and SQL.

Responsibilities

• Lead design and delivery of secure, reliable ML solutions.
• Partner with teams to define and ship features.
• Monitor production systems for quality.

Skills

ML algorithms expertise

Statistics and regression methods

NLP and convolutional neural networks

Python programming

SQL skills

Tools

TensorFlow

PyTorch

Jupyter Notebooks

Job description

Staff ML Engineer

• Pay Rate: $150.00 - $200.00/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
• Work Authorization: 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.

About the Role

We are looking for a Staff ML Engineer to serve as a technical anchor on a product team building machine learning systems at scale. This is a senior individual contributor role with significant influence over technical direction, architecture, and team capability. You will drive multiple ML initiatives simultaneously, mentor less experienced engineers, and help shape how the organization approaches AI and ML development.

Staff engineers here are leaders who still get hands dirty. You pair with teammates, influence architecture decisions, and own outcomes across the ML stack.

Responsibilities

• Delivery & Execution (approx. 45% of time)
  • Lead and contribute to the design and delivery of secure, reliable, and scalable ML solutions
  • Partner with product managers, engineers, and designers to define and ship well-scoped features
  • Evaluate and configure platforms and tools to meet current and future business needs
  • Build and maintain robust monitoring, alerting, and observability tooling
• Technical Strategy & Planning (approx. 20% of time)
  • Research and analyze business trends and usage signals to identify ML opportunities
  • Evaluate and recommend technology platforms, infrastructure, and ML architectures aligned to business requirements
  • Design infrastructure, network, database, and ML system architectures for new and evolving products
  • Contribute to project planning across multiple concurrent initiatives
  • Develop and deliver formal technical training for the team
• Continuous Learning (approx. 15% of time)
  • Participate in internal and external ML and software engineering communities
  • Attend conferences and technical forums; apply relevant innovations to team practice
  • Stay current on research and tooling at the frontier of ML engineering
• Support & Enablement (approx. 20% of time)
  • Serve as a senior technical resource for partner and support teams
  • Monitor production systems and maintain Service Level Objectives
  • Conduct regular reviews of system capacity, performance, and prediction quality

Qualifications

• 3–6 years of relevant ML engineering experience
• Deep expertise in ML algorithms: clustering, forecasting, anomaly detection, neural networks
• Strong command of statistics and regression methods
• Experience with advanced ML techniques: NLP, convolutional neural networks, autoencoders, embeddings
• Demonstrated experience training models on very large datasets
• Expert-level familiarity with ML tooling: Jupyter Notebooks, Pandas, SciPy, Scikit-learn, Gensim, TensorFlow, PyTorch
• Experience with GPU acceleration (CUDA, cuDNN)
• Experience with cloud ML platforms (e.g., Vertex AI, BigQueryML, AutoML) and data engineering at scale (BigQuery, distributed data stores)
• Proficiency in Python; experience with Node.js, HTML/CSS/JavaScript, React, and D3
• Expert SQL skills; experience with relational and NoSQL databases
• Strong Git and CI/CD proficiency
• Deep experience in Linux/Unix environments
• Experience designing scalable REST APIs and web service architectures
• Experience with production systems design: high availability, disaster recovery, performance optimization, and security
• Experience with cloud automation patterns and ML managed services
• Experience with defensive coding and high-availability patterns
• Experience with A/B testing methodologies
• Familiarity with advanced ML architectures: GANs, GRUs, LSTMs, RNNs, CNNs, style transfer

Core Competencies

• Strategic thinker who can connect technical decisions to business outcomes
• Leads through ambiguity; adapts plans as context evolves
• Develops others; actively builds the skills of junior and mid-level engineers
• Communicates with precision across all levels of the organization
• Drives innovation; comfortable challenging existing approaches
• Delivers outcomes across multiple concurrent workstreams

Equal Opportunity

We strive to build teams that reflect the diversity of the communities we work in. We encourage all qualified applicants to apply, including people from traditionally underrepresented groups such as women, visible minorities, Indigenous peoples, people identifying as LGBTQ2SI, veterans, and people with visible/nonvisible disabilities.

We have a dedicated webpage for accommodations where you can learn more about what we offer, and request accommodation: https://raise.jobs/accommodations/