About this opportunity
Ian Martin Group lists this Senior Applied ML Engineer opportunity in austin, Texas. Review the employer’s description below for duties, qualifications and application requirements.
Job description
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.
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. 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.
Responsibilities
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
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
Brings innovative thinking to product and technical challenges
Strong collaborator who actively supports team success
Drives results consistently; holds self to a high standard
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Worksite address
austin, TX, 78716, US
Who can apply
Review the original listing for work authorization, qualifications and employer requirements.