Sonatus
Staff DevOps/MLOps Engineer
Join
Sonatus
as a
Staff DevOps/MLOps Engineer
and lead the design, build, and scaling of our end‑to‑end DevOps and MLOps platform for AI‑driven automotive systems.
Role Summary In this leadership role you will own the entire cloud CI/CD pipeline, cloud infrastructure management, and machine learning model lifecycle. Your work will enable models to move from experimentation to production with velocity, reliability, and observability, driving the future of software‑defined vehicles.
Responsibilities
Design and build the foundational, end‑to‑end DevOps and MLOps platform for generative AI systems.
Implement full DevOps and MLOps frameworks, including CI/CD/CT automation (Continuous Integration/Delivery/Training) that takes models from experiment to production.
Deploy, scale, and optimise model‑serving infrastructure, managing GPU/NPU resources, minimizing inference latency, and ensuring robust monitoring.
Create cohesive best‑practice standards for the entire AI lifecycle, covering model versioning, infrastructure as code, and production observability.
Qualifications
8+ years of experience building and scaling production‑grade cloud services, with strong focus on DevOps, MLOps, and/or SRE.
Systems thinker capable of architecting end‑to‑end solutions and deep understanding of the full CI/CD pipeline and ML lifecycle.
Deep proficiency in Python and IaC tools such as Terraform or Pulumi.
Experience with MLOps tools (e.g., MLflow, Kubeflow, Vertex AI) and production‑monitoring frameworks.
Knowledge of reproducibility, approvals, audit trails, PII handling, model cards, and policy/compliance (privacy, evaluation, guardrails).
Hands‑on experience with public cloud platforms (GCP, AWS, Azure) and container orchestration (Docker, Kubernetes).
Experience deploying and operationalising ML pipelines, including blue/green or canary rollouts, feature/model registries, and automated retraining.
Knowledge of PyTorch, vLLMs, GPUs, and GPU/CPU util optimisation (quantization, batching).
Experience with vector databases (e.g., Pinecone, Weaviate) and embedding management from deployment and scaling perspectives.
Optional: experience building LLM systems, RAG pipelines, and attribution of agentic drift.
Benefits
Competitive salary ($168,500 – $232,000).
Stock option plan.
Health, dental, and vision insurance.
401(k) retirement plan.
Life insurance.
Unlimited paid time off.
Family leave (maternity, paternity).
Flexible work arrangements.
Free food and snacks in the office.
Sonatus is an equal‑opportunity employer. All qualified applicants will receive consideration without regard to race, color, religion, gender, sexual orientation, gender identity, national origin, or protected status.
To all recruitment agencies: Sonatus does not accept unsolicited agency resumes. Please do not forward resumes to our careers alias or other Sonatus employees.
#J-18808-Ljbffr
Sonatus
as a
Staff DevOps/MLOps Engineer
and lead the design, build, and scaling of our end‑to‑end DevOps and MLOps platform for AI‑driven automotive systems.
Role Summary In this leadership role you will own the entire cloud CI/CD pipeline, cloud infrastructure management, and machine learning model lifecycle. Your work will enable models to move from experimentation to production with velocity, reliability, and observability, driving the future of software‑defined vehicles.
Responsibilities
Design and build the foundational, end‑to‑end DevOps and MLOps platform for generative AI systems.
Implement full DevOps and MLOps frameworks, including CI/CD/CT automation (Continuous Integration/Delivery/Training) that takes models from experiment to production.
Deploy, scale, and optimise model‑serving infrastructure, managing GPU/NPU resources, minimizing inference latency, and ensuring robust monitoring.
Create cohesive best‑practice standards for the entire AI lifecycle, covering model versioning, infrastructure as code, and production observability.
Qualifications
8+ years of experience building and scaling production‑grade cloud services, with strong focus on DevOps, MLOps, and/or SRE.
Systems thinker capable of architecting end‑to‑end solutions and deep understanding of the full CI/CD pipeline and ML lifecycle.
Deep proficiency in Python and IaC tools such as Terraform or Pulumi.
Experience with MLOps tools (e.g., MLflow, Kubeflow, Vertex AI) and production‑monitoring frameworks.
Knowledge of reproducibility, approvals, audit trails, PII handling, model cards, and policy/compliance (privacy, evaluation, guardrails).
Hands‑on experience with public cloud platforms (GCP, AWS, Azure) and container orchestration (Docker, Kubernetes).
Experience deploying and operationalising ML pipelines, including blue/green or canary rollouts, feature/model registries, and automated retraining.
Knowledge of PyTorch, vLLMs, GPUs, and GPU/CPU util optimisation (quantization, batching).
Experience with vector databases (e.g., Pinecone, Weaviate) and embedding management from deployment and scaling perspectives.
Optional: experience building LLM systems, RAG pipelines, and attribution of agentic drift.
Benefits
Competitive salary ($168,500 – $232,000).
Stock option plan.
Health, dental, and vision insurance.
401(k) retirement plan.
Life insurance.
Unlimited paid time off.
Family leave (maternity, paternity).
Flexible work arrangements.
Free food and snacks in the office.
Sonatus is an equal‑opportunity employer. All qualified applicants will receive consideration without regard to race, color, religion, gender, sexual orientation, gender identity, national origin, or protected status.
To all recruitment agencies: Sonatus does not accept unsolicited agency resumes. Please do not forward resumes to our careers alias or other Sonatus employees.
#J-18808-Ljbffr