Senior Software Engineer - ML Ops

Jobgether

4d • $130,000 - $180,000 • Remote

About The Position

This role offers the chance to shape and maintain state-of-the-art machine learning and software infrastructure in a high-impact, fast-growing environment. The Senior Software Engineer will focus on building scalable MLOps pipelines, cloud-based deployment solutions, and production-ready ML systems, collaborating closely with data scientists and engineering teams. The position emphasizes technical leadership, problem-solving, and mentorship, providing opportunities to influence architecture, CI/CD pipelines, and model lifecycle management. The successful candidate will work on complex, distributed systems, optimize production environments, and contribute to continuous innovation while ensuring high-quality, secure, and maintainable solutions. This role balances hands-on engineering with strategic thinking in a dynamic, remote-first setting.

Requirements

• 5–7 years of software engineering experience, including production-level system deployment
• Strong Python development experience (2+ years) and familiarity with cloud computing environments (AWS preferred)
• Experience with containerized deployments using Docker and Kubernetes
• Knowledge of software architecture, design patterns, testing, version control, and CI/CD best practices
• Proficiency with infrastructure-as-code tools such as Terraform or AWS CDK
• Experience monitoring and optimizing production systems using tools like Datadog, ELK, Grafana, or Prometheus
• Participation in on-call rotations and handling operational escalations

Nice To Haves

• experience with machine learning frameworks (TensorFlow, PyTorch, XGBoost, Scikit-learn)
• ML lifecycle tools (MLflow, Kubeflow, Seldon Core)
• microservices/API development

Responsibilities

• Design, develop, test, and maintain software applications and MLOps pipelines, ensuring scalability, reliability, and high-quality code
• Lead technical initiatives, provide guidance to junior engineers, participate in architecture decisions, and conduct code reviews
• Build and maintain cloud-based ML infrastructure (AWS, Azure, GCP) and containerized deployments using Docker and Kubernetes
• Implement CI/CD pipelines and orchestration using tools such as GitLab CI, GitHub Actions, Circle CI, or Airflow
• Collaborate closely with data scientists to productionize, version, deploy, and monitor machine learning models, ensuring automated testing and quality assurance
• Stay current with emerging technologies and best practices, applying them to optimize software development processes and system performance
• Ensure software and infrastructure adhere to security standards, compliance requirements, and operational best practices

Benefits

• Competitive base salary range: $130,000 – $180,000 USD
• Equity opportunities and performance-based incentives
• Unlimited Paid Time Off (PTO) and flexible remote-first culture
• Comprehensive healthcare, vision, and dental plans, including employer contributions to Health Savings Accounts (HSA)
• Paid parental leave and family-focused perks, including diaper delivery for newborns
• Retirement plan with competitive 401(k) match
• Home office allowance and opportunities for professional development
• Wellness programs including Employee Assistance Program and 24/7 telemedicine access
• Regular team activities, social events, and in-person gatherings to foster collaboration and culture

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed