Data Engineering/MLOps Manager

Reposted 15 Days Ago
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Haifa
Mid level
Artificial Intelligence • Hardware • Internet of Things • Machine Learning • Software • Manufacturing
We are transforming how people and machines work together to push the boundaries of human productivity.
The Role
Lead a team in building scalable AI infrastructure, develop CI/CD pipelines for AI workflows, mentor engineering staff, and drive continuous improvement in DataOps and MLOps.
Summary Generated by Built In

Our mission is to provide manufacturers and other industrial sectors with insights into the health of machines, processes, and operations to transform how people work and what they can create. A leader in Machine Health and Process Health solutions, Augury uses purpose-built AI technology, trained by industry experts and the world’s largest data library, to help companies realize the full potential of their production. Together with our customers, we are pioneering Production Health by removing friction created by competing business goals so companies can improve business outcomes, empower their workforce, and achieve sustainable production- all at the same time. 

You are a Data Engineering/MLOps Manager who thrives at the intersection of cutting-edge AI and scalable infrastructure. In this role, you'll lead a team of forward-thinking engineers to build and evolve the backbone of our GenAI capabilities, from real-time inference pipelines and LLMOps frameworks to scalable data platforms and CI/CD systems. You’ll collaborate closely with Data Science, AI, and Product teams to bring innovative GenAI use cases to life, all while fostering a culture of experimentation, technical excellence, and continuous learning. If you're passionate about enabling AI teams, pushing the boundaries of what’s possible with modern data architectures, and mentoring others to do the same, we want to hear from you.

A Day In Your Life

  • Collaborate closely with Data Science, AI, and Product teams to build infrastructure that supports their evolving needs, including GenAI pipelines (RAG, fine-tuning, LLMOps). 
  • Build and maintain core infrastructure to support real-time predictions and GenAI inference workflows in production. 
  • Develop CI/CD pipelines for both Big Data and AI/LLM components, including automated testing, monitoring, and deployments for AI workflows. 
  • Tackle core performance challenges related to data pipeline scalability, GenAI model serving, and vector data operations. 
  • Continuously adapt the data infrastructure vision & strategy, ensuring readiness for new AI/GenAI use-cases, evolving data scales, and business demands. 
  • Drive implementation of holistic technologies and tools (e.g., Feature Stores, Vector Databases, Prompt Stores) to enable data and AI teams’ autonomy. 
  • Lead, mentor, and develop the Data Engineering and MLOps team with a focus on GenAI mindset and modern data architectures. 
  • Own the hiring process for Data Engineers and MLOps specialists, collaborating with key stakeholders to build a high-performance team. 
  • Define and implement strategies for continuous improvements in DataOps, MLOps, and LLMOps workflows.

What You Bring

  • Leadership & mentoring in the context of AI/GenAI team enablement. 
  • Strong interpersonal and cross-functional communication. 
  • Ability to quickly research and implement AI/GenAI tools & technologies (MVP/PoC-driven approach). • Strong problem-solving mindset, with a focus on AI workload optimization. 
  • Team player with a passion for pushing technological boundaries.
  • Opinion leader with a strong GenAI curiosity. 
  • Natural enabler of cross-functional AI-driven collaboration. 
  • Great listener who thrives on understanding team and business needs. 
  • Persistent and strategic thinker (marathonist mindset).

Perks

  • Stock options
  • Paid parental leave
  • Flex PTO
     

Augury is a people-first organization. We believe in fostering an inclusive environment in which employees feel encouraged to share their unique perspectives, leverage their strengths, and act authentically. We know that diverse teams are strong teams, and we welcome those from all backgrounds and varying experiences. We are committed to providing employees with a work environment free of discrimination and harassment. We believe that diversity is more than just good intentions, and we are committed to creating an inclusive environment for all employees.

Augury is a proud equal opportunity employer, we strive to create a work environment in which everyone, all applicants, employees, customers, guests, and vendors feel safe and comfortable. We commit to maintain a workplace that is free of any type of harassment and does not tolerate anyone intimidating, humiliating, or hurting others. We prohibit willful discrimination based on age, gender, ethnicity, race, color, religion, political opinions, sexual orientation, sexual identity or expression, military or veteran status, disability or any other characteristic protected by law.

Top Skills

AI
Big Data
Ci/Cd
Data Pipelines
Feature Stores
Genai
Llmops
Vector Databases

What the Team is Saying

Fernando
Grace
Danielle
Angela
Brandon
Hari
Einat
Gal
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The Company
HQ: New York, NY
203 Employees
Year Founded: 2011

What We Do

Our mission is to provide manufacturers and other industrial sectors with insights into the health of machines, processes, and operations to transform how people work and what they can create. A pioneer in Machine Health and Process Health solutions, we use purpose-built AI, trained by industry experts and the world’s largest data library, to help customers eliminate production downtime, improve process efficiency, maximize yield, and reduce waste and emissions.

Why Work With Us

We believe the best perk is who you work with, professionally and personally. Our team is a diverse group of people that breed creative thinking and want to solve big challenges together. Each person understands the impact of their role on our customers and Augury's success.

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Augury Offices

Remote Workspace

Employees work remotely.

Typical time on-site: None
HQNew York, NY
Haifa, Israel
Tel Aviv, Israel
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