Senior Machine Learning Engineer

Contingent work is an excellent fit for individuals seeking career flexibility and non-traditional work arrangements, while still being highly motivated to deliver exceptional results in dynamic, high-profile environments. In this assignment, you will be working with Coinbase through our Managed Service Provider—partnering with one of the most influential cryptocurrency companies in history, dedicated to empowering their customers’ success through innovative solutions.

• Architect AI Solutions: Design and deploy scalable, secure systems leveraging state-of-the-art LLMs and deep learning to solve complex organizational challenges.
• Drive Technical Execution: Lead project lifecycles by managing priorities, deadlines, and high-impact deliverables with a focus on technical excellence.
• Engineer High-Quality Code: Develop robust, well-tested Python applications that bridge the gap between advanced AI research and practical business needs.
• Set the Standard: Establish best practices for system design, coding standards, and the strategic adoption of AI productivity tools across the team.
• Mentor & Multiply: Act as a technical touchstone, mentoring team members on architectural integrity and modern AI/ML development workflows.
• Optimize & Scale: Proactively troubleshoot and resolve complex technical bottlenecks to enhance system reliability and operational efficiency.
• Cross-Functional Leadership: Conduct rigorous design reviews to ensure every feature meets the highest standards for security, scalability, and performance.
• Experience: 5+ years of professional experience in machine learning and software engineering, with a track record of shipping production-grade services.
• ML Fluency: Hands-on expertise in modern AI architectures (LLMs, GNNs, Deep Learning) as well as classical modeling (Gradient Boosting, Regression).
• The AI Stack: Deep proficiency with the Generative AI ecosystem, specifically LangGraph, LangSmith, Google ADK, Google Vertex AI and AWS bedrock.
• Domain Expertise: Specialized knowledge in at least one area: NLP, Information Retrieval, Computer Vision, or Advanced Statistical Modeling.
• Engineering Rigor: Ability to write clean, maintainable, and highly-tested code (Python) that directly solves customer pain points.
• Communication: Exceptional written and verbal communication skills; ability to translate complex technical concepts for non-technical stakeholders.
• Mission-Driven: A genuine passion for building an open, global financial system.
• Education: Advanced degree (Master’s or PhD) in CS, ML, Statistics, or a related quantitative field.
• Data Infrastructure: Experience with large-scale data tools such as Spark , Kafka/Kinesis , Snowflake , or Databricks .
• Workflow Orchestration: Familiarity with Apache Airflow or similar DAG-based orchestration tools.
• Ethical AI: Deep understanding of model interpretability, bias mitigation, and responsible AI governance.
• Expertise in data analysis and visualization.
  Equal Opportunity Employer
  Magnit Global is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, creed, religion, sex, sexual orientation, national origin or nationality, ancestry, age, disability, gender identity or expression, marital status, veteran status, or any other category protected by law. In addition, all qualified applicants with arrest or conviction records will be considered for employment in accordance with legal requirements.