Senior Applied ML Engineer

About the role

We are hiring a Senior Applied ML Engineer to join a product-focused team building machine learning solutions at scale. In this role, you will contribute hands-on engineering alongside mentorship and technical leadership.

Responsibilities

• 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
• Audit off-the-shelf tools and platforms to fit evolving requirements
• Create instrumentation, including dashboards, alerts, and logging, to enable proactive operations
• Participate in internal communities of practice and external learning forums
• Independently research emerging ML techniques and tooling to inform team decisions
• Serve as a resource for partner teams and support functions
• Maintain awareness of Service Level Objectives
• Assess system capacity, prediction quality, and overall production health regularly

Qualifications

• 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, SciPy, Scikit-learn, Gensim, TensorFlow, PyTorch
• Experience with a major cloud ML platform (e.g., Vertex AI, BigQueryML) and data engineering tools such as BigQuery
• 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 NoSQL 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

Core Competencies

• Operates independently with minimal direction
• Navigates complexity and ambiguity with confidence
• Communicates clearly in technical and cross-functional settings
• Bridges gaps between different teams and departments
• Brings innovative thinking to product and technical challenges
• Drives results consistently; holds self to a high standard