Senior Machine Learning Engineer, Enterprise AI Systems

This is a fully remote position, open to applicants in United States.

📋 Description

• Become a member of a product team and engage in software design, algorithm development, and the complete product lifecycle.

• Develop and integrate AI/ML algorithms directly into software solutions.

• Collaborate with business stakeholders, technology infrastructure teams, and development groups to fulfill business objectives.

• Conduct performance tuning, testing, product monitoring, and data engineering tasks.

• Create, maintain, and deploy production applications.

• Review submitted code and offer feedback based on industry best practices.

• Work alongside UX, engineering, and product management to develop secure, reliable, and scalable machine learning solutions.

• Document processes, review outputs, and ensure adherence to quality and change control standards.

• Guarantee user stories are developer-ready, comprehensible, and testable.

• Write code or scripts to automate infrastructure, monitoring services, test cases, and destructive testing processes.

• Configure commercial off-the-shelf solutions to meet business requirements.

• Develop dashboards, logging mechanisms, alert systems, and proactive responses.

• Address inquiries from product and support teams while fostering collaboration.

• Provide application support for production-level software.

• Monitor production Service Level Objectives.

• Evaluate production performance and capacity across code, infrastructure, data, message processing, and prediction quality.

⛳️ Requirements

• Must be at least eighteen years old.

• Must have legal authorization to work in the United States.

• Minimum educational qualification: high school diploma and/or GED.

• At least 2 years of relevant work experience.

• Preferred: 5+ years of experience in Machine Learning Engineering, AI Engineering, Software Engineering, or a related discipline.

• Familiarity with designing Agentic AI applications, LLM-powered solutions, RAG systems, and intelligent automation workflows.

• Experience with knowledge graphs, graph engineering, network analysis, semantic search, and enterprise knowledge layers.

• Expertise in creating scalable data pipelines, data products, and feedback loop architectures.

• Proficiency in Python, PyTorch, TensorFlow, Scikit-learn, Pandas, and related technologies.

• Experience with cloud-native AI/ML platforms, particularly Google Cloud Platform, Vertex AI, BigQuery, and BigQuery ML.

• Knowledge of model deployment, monitoring, and MLOps practices.

• Experience in building and maintaining vector databases, model serving platforms, APIs, microservices, distributed systems, and high-availability architectures.

• Strong grasp of CI/CD, version control, automated testing, security, and performance optimization.

• Experience handling large-scale structured and unstructured datasets, SQL, NoSQL, and contemporary data architecture patterns.

• Excellent communication, collaboration, and stakeholder management abilities.

• Capability to influence technical decisions across engineering, data, analytics, and product teams.

• Ability to excel in ambiguous environments, grasp emerging technologies, tackle complex challenges, and foster innovation.

🏝️ Benefits

• Remote/Virtual work arrangement.

• Overnight travel typically required 5% to 20% of the time.