Member of Technical Staff – Software Engineer

Jobtailor; Palo Alto (CA); On-site; USD 180,000 - 280,000; Full time

Job summary

Jobtailor in Palo Alto seeks an experienced systems engineer to design and develop pipelines and tools that make the product operational, accelerating deployment by moving code from development to production, and orchestrating data flows across the deployed product.

You will build scalable features and APIs for complex engineering workflows, set up MLOps infrastructure for training geometry and physics data, contribute to product strategy with early customers, and own critical features from

Qualifications

• 6+ years of experience in high performance computing environments.
• Proficiency in C++ and Python.
• Experience with gRPC, Protocol Buffers, Docker, Kubernetes, and Bazel or similar build systems.
• Cloud compute for data generation and enabling data science teams to train models with MLOps is a plus.
• CUDA experience is advantageous but not required.

Responsibilities

• Design and develop pipelines and tools that make the product operational.
• Accelerate development by building systems that move code from development to deployment.
• Orchestrate data flows throughout the deployed product.
• Develop scalable product features and APIs for complex engineering workflows.
• Set up and integrate MLOps infrastructure for training deep learning models on geometry and physics data.
• Assist with product strategy, roadmap planning, and prioritization with early customers.

Skills

HPC Experience

MLOps

C++ & Python

Cloud Computing

Autonomy

Ownership

Tools

C++

Python

GRPC

Protocol Buffers

Docker

Kubernetes

Bazel

Cloud Computing

MLOps

CUDA

Job description

• Design and develop pipelines and tools that make the product operational
• Accelerate development by building systems that move code from development to deployment
• Orchestrate data flows throughout the deployed product
• Develop scalable product features and APIs for complex engineering workflows
• Set up and integrate LLM or VLM infrastructure
• Establish an MLOps framework for training deep learning architectures on geometry and physics data
• Assist with product strategy, roadmap planning, and prioritization in partnership with early customers and design partners
• Build and ship critical product features
• Learn and contribute while building products for engineers

Requirements

• 6+ years of experience developing and shipping features in high performance computing
• Proficiency in C++, Python, or another language necessary for setting up a system
• Experience with gRPC, Protocol Buffers, Docker, Kubernetes, and Bazel or another language-agnostic build system
• Proficiency using cloud compute for data generation, scraping, and enabling data science teams to train models with MLOps is a plus
• CUDA experience is advantageous but not required
• Frontend experience is a plus
• Startup experience is a strong advantage
• Interest in entrepreneurship and taking products from 0 to 1
• Continuous learning mindset
• Interest in building geometry- and physics-based models for design problems
• Ability to work with autonomy and ownership

Core Competencies

Demonstrates expertise in developing and shipping features for high performance computing, with a strong focus on MLOps frameworks and building scalable product features and APIs. Proficient in C++, Python, and cloud computing, with a continuous learning mindset and a passion for entrepreneurship.

Highest-signal resume keywords

• High Performance Computing Experience
• MLOps Framework Development
• Proficiency in C++ and Python
• Experience with Docker and Kubernetes
• Startup Experience

Hard Skills

• C++
• Python
• GRPC
• Protocol Buffers
• Docker
• Kubernetes
• Bazel
• Cloud Computing
• MLOps
• CUDA

Soft Skills

• Continuous Learning Mindset
• Autonomy
• Ownership

Industry Keywords

• Deep Learning Architectures
• Geometry Models
• Physics Data
• Product Strategy
• Roadmap Planning