Senior Data & MLOps Engineer

Responsibilities

We are representing a confidential cloud infrastructure organization seeking a Senior Data & MLOps Engineer in London. In this role, you will design and scale the infrastructure supporting an advanced reliability platform that processes telemetry data, derives meaningful metrics, identifies anomalies, predicts potential issues, and enables automated root cause analysis across distributed systems.

Your responsibilities will include:

• Design and implement scalable data ingestion pipelines for high-throughput streaming and telemetry data
• Build feature processing and baseline computation systems for time-series data
• Productionize machine learning models for prediction and anomaly detection
• Develop and operate low-latency services and robust offline workflows
• Architect horizontally scalable microservices with clear separation between components, leveraging orchestration technologies
• Implement monitoring and feedback loops for continuous model and signal improvement
• Collaborate with Platform, Infrastructure, and Fleet teams to integrate operational signals into monitoring and diagnostics
• Scale systems from proof-of-concept to production-grade, fleet-level deployments
• Implement scalable solutions for mitigation and structured analysis

What We're Looking For

Required qualifications:

• 7+ years of experience in data engineering, distributed systems, MLOps, or infrastructure ML roles in production environments
• Proven experience building high-throughput streaming or telemetry pipelines (Kafka, Pulsar, Kinesis, or equivalent)
• Strong experience designing time-series feature pipelines and operating large-scale observability systems
• Experience building and maintaining feature stores and ensuring offline/online feature parity
• Hands-on experience deploying ML models to production, including versioning, monitoring, rollback, and drift detection
• Experience designing scalable microservices deployed in Kubernetes-based environments
• Strong proficiency in Python and at least one systems language (Go, Rust, or C++)
• Experience working with distributed compute or training systems (NCCL, PyTorch Distributed, Spark, Ray, Slurm)
• Familiarity with GPU telemetry systems such as NVML or DCGM and hardware-level monitoring concepts
• Demonstrated experience scaling systems from proof-of-concept to production-grade deployments

Preferred qualifications:

• Experience working on GPU fleet management, hyperscale infrastructure, or AI training clusters
• Experience building anomaly detection or failure prediction systems for hardware or distributed systems
• Experience implementing distributed straggler detection or collective-level performance analysis systems
• Experience developing agentic or LLM-powered reasoning systems for diagnostics or operational intelligence
• Background in reliability engineering or SRE practices

You'll thrive in this role if:

• You love building systems that turn raw infrastructure telemetry into actionable intelligence
• You're curious about distributed systems failure modes, GPU performance pathologies, and reliability engineering at scale
• You're excited by the idea of moving from anomaly detection to prediction to autonomous root cause reasoning
• You enjoy designing platforms that protect uptime, revenue, and customer trust through proactive systems thinking

How We Work With You

Our talent team at Get A Job.ai will guide you through the entire process. When you apply through our platform, a dedicated recruiter will screen your application and conduct an initial conversation to understand your background and career goals. Once we determine there's a strong fit, we'll submit your profile to our client for consideration and coordinate all subsequent interview stages.

Please apply exclusively through Get A Job.ai. Do not attempt to contact the client organization directly, as this may disqualify your application.

Pay

Compensation details will be discussed during the screening process with our recruiting team.

Equal Opportunity

Get A Job.ai is committed to fostering an inclusive recruitment process. We welcome applications from all qualified candidates regardless of race, color, religion, sex, disability, age, sexual orientation, gender identity, national origin, veteran status, or any other protected characteristic.