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MLOps Engineer at LockedIn AI, Remote (United States)

As an MLOps Engineer at LockedIn AI, you will design and manage the infrastructure that powers ML models from development to production. Your work ensures that models are deployed safely, monitored continuously, and optimized for performance at scale.

You will build robust pipelines, automate ML workflows, and ensure system reliability for latency-sensitive AI applications serving millions of users.

Key Responsibilities

ML Lifecycle Ownership

• Manage end-to-end model deployment for LLMs, RAG systems, and speech models
• Build scalable inference infrastructure with low latency and high availability
• Implement versioning, model registries, and deployment strategies (A/B, canary, rollback)

ML Pipeline Automation

• Design CI/CD pipelines for training, testing, validation, and deployment
• Automate retraining workflows triggered by drift or data updates
• Ensure ML workflows are fully reproducible and test-driven

Monitoring & Reliability

• Build real-time monitoring systems for model performance and latency
• Detect data drift and performance degradation early
• Set up alerting systems and dashboards for operational visibility

Infrastructure & Scaling

• Manage GPU-based compute environments and cloud infrastructure
• Optimize inference cost, storage, and token usage
• Use Docker and Kubernetes for scalable ML workloads

Data & Feature Systems

• Build data pipelines for training and validation workflows
• Implement data versioning and lineage tracking
• Collaborate on feature store design and data quality systems

Security & Governance

• Ensure secure handling of data and model artifacts
• Implement access control, encryption, and audit trails
• Maintain compliance and governance across ML systems

Required Qualifications

• 3+ years in MLOps, ML engineering, or DevOps with ML systems
• Strong Python experience with ML frameworks (PyTorch, TensorFlow, etc.)
• Experience with Docker, Kubernetes, and cloud platforms (AWS/GCP/Azure)
• Hands-on experience building ML CI/CD pipelines
• Familiarity with ML monitoring tools and production systems
• Experience working with data scientists and engineering teams

Preferred Skills

• Experience with LLM deployment and real-time AI systems
• Knowledge of distributed training and GPU infrastructure
• Experience with ML observability tools (Arize, WhyLabs, etc.)
• Background in startup or high-growth environments
• Familiarity with prompt/version management and RAG systems

What We Offer

• Competitive salary: $140,000 – $200,000 USD
• Early-stage equity ownership
• Remote-first flexibility (US-based)
• High-impact role in a 1M+ user AI platform
• Fast-paced, AI-native engineering environment
• Opportunity to build production-scale ML systems from scratch

Why Join LockedIn AI?

LockedIn AI is redefining how candidates succeed in interviews using real-time AI assistance. You’ll work on systems that directly power live AI copilots, shaping the future of career technology.

Category-defining AI interview platform
Massive and rapidly growing global user base
Real-time ML systems at scale
Strong engineering culture focused on speed and impact

How to Apply

Please submit:

• Updated resume/CV
• Short note explaining interest in LockedIn AI
• Links to GitHub, projects, or technical work (optional but encouraged)