Software Engineer - AI/ML applications

Job Title:Software Engineer - AI/ML applications

Location:Santa Clara, CA

Duration:1 year

# of Roles: 1

Note: This is a W2 only role — C2C, C2H will not be considered

The team is looking for a strong software engineer, not an ML researcher. There''s already plenty of ML/DL depth in house, so no deep learning or fine-tuning experience is required. The priority is a hands-on coder rather than a lead — someone who collaborates closely with research. Strong software design skills are essential, particularly CI/CD architecture that can support external open-source contributions, along with solid infrastructure and scale experience.

• Strong Python programming
• Familiarity with automation testing and CI/CD pipelines
• Backend infrastructure: Slurm, Ray, Kubernetes; containerization
• Synthesizing large data sets
• Security automation — security libraries, running security scanners to find vulnerabilities
• Currently hands-on coding, not someone who has worked in a lead role for the past few years

Ask: Please prioritize hands-on Python engineers with CI/CD and distributed infrastructure depth. Screen out ML research-heavy profiles and candidates whose recent experience has been primarily in a lead capacity.

Focus areas for the role

• Introducing automated testing and automated scanning
• Deploying and scaling on distributed infrastructure

Interview process — 3 rounds total

• A HackerRank-style coding assessment to validate background
• A WWT engineer round focused on Python coding and vetting other software design components
• A hiring manager round covering system design, software engineering, and culture
• Hands-on coding, problem solving, and system design are assessed throughout all rounds.

Who we are What will you be doing?

Position Overview: We are seeking a Software Engineer (Contract) specializing in Artificial Intelligence and Machine Learning applications to independently drive the development, evaluation, deployment, and lifecycle management of AI powered systems. This role combines advanced AI application development, software engineering, automation, and distributed infrastructure management. The successful candidate will leverage AI agents, build automated testing frameworks, implement secure GitLab continuous integration and continuous delivery pipelines, and deploy scalable AI solutions across distributed environments.

Responsibilities:

• Architect, deploy, and scale open source models using Kubernetes, Ray, or Slurm to support highly available and fault tolerant AI workloads.
• Design experiments, perform prompt tuning, evaluate model performance, and deploy production ready AI models and agents.
• Build flexible model benchmarking capabilities that enable rapid testing and replacement of models based on evolving business requirements.
• Conduct comprehensive benchmarking, error analysis, and gap analysis on model outputs and communicate findings through dashboards and reporting.
• Develop automated testing frameworks that validate end to end application functionality and improve test coverage across software and AI generated outputs.
• Automate vulnerability scanning and security validation within GitLab merge request workflows.
• Build and maintain remediation pipelines to address security findings efficiently.
• Own features from concept through production, including architectural decisions, repository management, and community engagement when applicable.
• Optimize distributed AI infrastructure for scalability, resilience, throughput, and low latency performance.
• Collaborate with technical and business stakeholders to ensure successful delivery of AI enabled solutions. 

Qualifications: Required Qualifications

• 4 or more years of professional experience developing production grade Python applications.
• Strong expertise in asynchronous Python development and clean software architecture principles.
• Experience deploying and operating production AI or machine learning models.
• Hands on experience with Kubernetes, Ray, Slurm, or similar distributed orchestration platforms.
• Strong understanding of GPU resource management and AI inference optimization.
• Experience with LangChain, Hugging Face, vLLM, and SGLang frameworks.
• Proven experience with prompt engineering, model evaluation, benchmarking, and large language model assessment methodologies.
• Proficiency with Python data analysis libraries, including pandas and NumPy.
• Advanced experience designing and maintaining GitLab continuous integration and continuous delivery pipelines.
• Experience integrating automated testing and vulnerability scanning within development workflows.
• Expert knowledge of PyTest, mocking frameworks, and automated test generation approaches.
• Advanced Git knowledge, including repository synchronization, commit signing, rebasing, and complex branching strategies.
• Strong communication skills with the ability to translate technical findings into business relevant insights.

Preferred Qualifications

• Experience deploying AI workloads across multi node cluster environments.
• Experience creating AI agents or multi agent systems.
• Experience contributing to open source AI communities and repositories.
• Experience building analytics dashboards for model performance monitoring.

Tools and Technologies: Python, Kubernetes, Ray, Slurm, LangChain, Hugging Face, vLLM, SGLang, GitLab, PyTest, pandas, NumPy, Git, GPU Infrastructure, Continuous Integration, Continuous Delivery, Artificial Intelligence Agents, Large Language Models, Automated Testing Frameworks, Security Automation, Model Benchmarking, Data Analytics.