Senior Mlops Platform Architect

We are hiring a senior MLOps/DevOps/SRE hybrid who can build an entire AI platform infrastructure end-to-end. This is not a research role and not a standard ML Engineer role. If you haven’t designed production-grade MLOps infrastructure, haven’t built CI/CD for ML, or haven’t deployed ML workloads on Kubernetes at scale, this role is not a fit.

You will design, build, and own the AWS-based infrastructure, Kubernetes platform, CI/CD pipelines, and observability stack that supports our AI models (Agentic AI, NLU, ASR, Voice Biometrics, TTS). You will be the technical owner of MLOps infrastructure decisions, patterns, and standards.

**Location**:Remote -**Europe (PL/ES/PT/CZ/CY)

**Key Responsibilities**:
**MLOps Platform Architecture (from scratch)**

- Design and build AWS-based AI/ML infrastructure using **Terraform (required)**.
- Define standards for security, automation, cost efficiency, and governance.
- Architect infrastructure for ML workloads, GPU/accelerators, scaling, and high availability.

**Kubernetes & Model Deployment**

- Architect, build, and operate production Kubernetes clusters.
- Containerize and productize ML models (Docker, Helm).
- Deploy latency-sensitive and high-throughput models (ASR/TTS/NLU/Agentic AI).
- Ensure GPU and accelerator nodes are properly integrated and optimized.

**CI/CD for Machine Learning**

- Build automated training, validation, and deployment pipelines (GitLab/Jenkins).
- Implement canary, blue-green, and automated rollback strategies.
- Integrate MLOps lifecycle tools (MLflow, Kubeflow, SageMaker Model Registry, etc.).

**Observability & Reliability**

- Implement full observability (Prometheus + Grafana).
- Own uptime, performance, and reliability for ML production services.
- Establish monitoring for latency, drift, model health, and infrastructure health.

**Collaboration & Technical Leadership**

- Work closely with ML engineers, researchers, and data scientists.
- Translate experimental models into production-ready deployments.
- Define best practices for MLOps across the company.

**Qualifications and Skills**:

- **5+ years** in a Senior DevOps, SRE, or MLOps Engineering role supporting production environments.
- Strong experience designing, building, and maintaining **Kubernetes clusters** in production.
- Hands-on expertise with **Terraform** (or similar IaC tools) to manage cloud infrastructure.
- Solid programming skills in **Python or Go** for building automation, tooling, and ML workflows.
- Proven experience creating and maintaining **CI/CD pipelines** (GitLab or Jenkins).
- Practical experience deploying and supporting **ML models** in production (e.g., ASR, TTS, NLU, LLM/Agentic AI).
- Familiarity with ML workflow orchestration tools such as **Kubeflow**, **Apache Airflow**, or similar.
- Experience with experiment tracking and model registry tools (e.g., **MLflow**, **SageMaker Model Registry**).
- Exposure to deploying models on **GPU** or specialized hardware (e.g., **Inferentia**, **Trainium**).
- Solid understanding of cloud infrastructure on **AWS**, including networking, scaling, storage, and security best practices.
- Experience with deployment tooling (Docker, Helm) and observability stacks (Prometheus, Grafana).

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**Ways to Know You’ll Succeed**:

- You enjoy building platforms from the ground up and owning technical decisions.
- You’re comfortable collaborating with ML engineers, researchers, and software teams to turn research into stable production systems.
- You like solving performance, automation, and reliability challenges in distributed systems.
- You bring a structured, pragmatic, and scalable approach to infrastructure design.

- Energetic and proactive individual, with a natural drive to take initiative and move things forward.
- Enjoys working closely with people - researchers, ML engineers, cloud architects, product teams.
- Comfortable sharing ideas openly, challenging assumptions, and contributing to technical discussions.
- Collaborative mindset: you like to build together, not work in isolation.
- Strong ownership mentality - you enjoy taking responsibility for systems end-to-end.
- Curious, hands-on, and motivated by solving complex technical challenges.
- Clear communicator who can translate technical work into practical recommendations.
- Thrives in a fast-paced environment where you can experiment, improve, and shape how things are done.

**What we offer**

- Competitive fixed compensation based on experience and expertise.
- Work on cutting-edge AI systems used globall.
- Dynamic, multi-disciplinary teams engaged in digital transformation.
- Remote-first work model

- Long-term B2B contract
- 20+ days paid time off
- Apple gear
- Training & development budget

**Our Core values at TheHRchapter**
️ Transparency: We believe in transparent and smooth recruitment processes. You will get feedback from us.

️ Diversity and inclusion: There is no place for discrimination and intolerance. We care about diversity aw