2 месяца назад
MLOps Engineering Lead (AI)
Вакансия из Hirify Global, списка международных tech-компанийДля мэтча и отклика нужен Plus
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
MLOps Engineering Lead (AI): Building scalable ML infrastructure, automated training and deployment pipelines, and low-latency model-serving systems for enterprise foundation models with an accent on technical leadership, inference architecture, and operational reliability. Focus on designing high-throughput serving platforms, feature stores, observability, and production workflows that bridge research experimentation with enterprise AI deployments.
Location: Remote in Europe or Israel
Company
is an AI company developing NEXUS, a large tabular model for enterprise decision-making.
What you will do
- Lead and mentor an MLOps engineering team and drive the MLOps roadmap.
- Define standards and architecture for ML infrastructure, deployment, operations, and tooling.
- Build scalable machine learning pipelines, CI/CD workflows, orchestration frameworks, and model-serving infrastructure.
- Design low-latency, high-throughput inference architecture using serving platforms such as Triton, TorchServe, TensorFlow Serving, and KServe.
- Develop feature stores, data pipelines, scalable storage, and observability strategies for model performance, drift, and system reliability.
- Partner with research teams to move experimentation into production.
Requirements
- Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field, or equivalent practical experience.
- 7+ years of MLOps experience, including 3+ years in a technical leadership role.
- Strong Python software engineering skills and experience with Bash and/or Go.
- Experience building MLOps infrastructure from the ground up and leading high-performing MLOps or infrastructure teams.
- Deep experience with ML platforms and frameworks, model serving, data pipelines, Kubernetes on AWS, GCP, or Azure, and infrastructure as code with Terraform, Helm, or GitOps.
- Strong communication skills and the ability to translate between research and production contexts.
Nice to have
- Experience with Kubeflow, Airflow, Argo Workflows, FastAPI, Databricks, or Snowflake.
- Experience serving and optimizing LLMs or foundation models.
- Exposure to SRE practices, cloud security certifications, or scaling ML infrastructure in AI startups.
Culture & Benefits
- Competitive compensation with salary and equity.
- Comprehensive health coverage for employees and dependents.
- Paid parental leave for all new parents, including adoptive and surrogate journeys.
- Relocation support for moves to office locations.
- Mission-driven, low-ego culture focused on diverse perspectives, ownership, and bias toward action.
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