Everyone is welcome at Handshake. We know diverse teams build better products and we are committed to creating an inclusive culture built on a foundation of respect for all individuals. We strongly encourage candidates from non-traditional backgrounds, historically marginalized or underrepresented groups to apply.

Your impact

At Handshake, we are assembling a diverse team of dynamic engineers who are passionate about creating high-quality, impactful products. As an ML Infrastructure Engineer, you will play a key role in driving the architecture, implementation, and evolution of our rapidly growing Machine Learning platform. Your technical expertise and leadership will be instrumental in helping millions of students discover meaningful careers, irrespective of their educational background, network, or financial resources.

Our primary focus is on building scalable ML infrastructure that empowers our Machine Learning and Relevance teams to iterate quickly and rapidly deploy ML solutions into various surfaces in our product stack.

Your experience

• Strong software engineering foundations: Experience with object-oriented and functional programming languages in production (Python, Golang), software design patterns, testing strategies and dev/ops practices (CI/CD). 
• Cloud platform expertise: Hands-on experience with cloud-based technologies. This includes tools like BigQuery, Cloud Storage, infrastructure-as-code tooling (Terraform) and an ML stack (Vertex, SageMaker, Ray, or similar) for handling machine learning workflows.
• ML aptitude: Experience building product features with ML frameworks like Scikit-Learn, PyTorch, TensorFlow and big data tooling like Spark.
• Problem-solving prowess: Outstanding problem-solving skills, with the ability to navigate complex machine learning infrastructure challenges and propose innovative, effective solutions.
• Teamwork oriented: A collaborative approach to work, coupled with the ability to communicate complex machine learning concepts effectively to both technical and non-technical stakeholders, and take input from Relevance stakeholders to guide implementation details.

Bonus areas of expertise

• ML infrastructure experience: Experience designing, implementing, and managing components of production ML infrastructure including:
  • • Real-time/batch ML model prediction and inference
    • Cluster management and deployment, deployment of GPU based training jobs
    • Familiarity with vector search tooling (Elasticsearch, Pinecone, etc…)
    • Creating or developing Feature Store components (offline/online stores and feature registry technologies)
    • Building ML search or ML recommendations systems
• Containerization and orchestration: Familiarity with containerization technologies like Docker and container orchestration platforms like Kubernetes.
• Generative AI (LLMs): Familiarity working with large language models such as ChatGPT, LLaMa, or Bard for text generation and Natural Language Processing (NLP) tasks.
• Streaming data processing: Experience with streaming data processing platforms such as Apache Beam or Apache Flink 

Compensation range

$150,000-$190,000

For cash compensation, we set standard ranges for all U.S.-based roles based on function, level, and geographic location, benchmarked against similar stage growth companies. In order to be compliant with local legislation, as well as to provide greater transparency to candidates, we share salary ranges on all job postings regardless of desired hiring location. Final offer amounts are determined by multiple factors, including geographic location as well as candidate experience and expertise, and may vary from the amounts listed above.

About us

Handshake is the #1 place to launch a career with no connections, experience, or luck required. The platform connects up-and-coming talent with 750,000+ employers - from Fortune 500 companies like Google, Nike, and Target to thousands of public school districts, healthcare systems, and nonprofits. In 2022 we announced our $200M Series F funding round. This Series F fundraise and valuation of $3.5B will fuel Handshake’s next phase of growth and propel our mission to help more people start, restart, and jumpstart their careers.

When it comes to our workforce strategy, we’ve thought deeply about how work-life should look at Hands