Machine Learning Infrastructure Engineer, Handshake
$150-190k
+ Equity
College career network and job board
Be an early applicant
College career network and job board
501-1000 employees
Be an early applicant
$150-190k
+ Equity
501-1000 employees
Company mission
To democratize access to opportunity and ensure any student can build a great career no matter who they know, where they live or what school they attend.
Role
Who you are
- 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
Desirable
- 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
What the job involves
- 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
Our take
The three founders of Handshake established their company in an attempt to eliminate inequality and make the student hiring landscape fairer. The Handshake platform acts as a LinkedIn for college students, pairing students from every walk of life with more than 650K employers, including the entire Fortune 500, which includes Google and Nike.
The graduate recruitment platform is open to any student with a valid @.edu email address, with more than 12 million active users from thousands of colleges and universities. With a student-first philosophy, the company generates revenue from both universities and employers rather than students.
Valued at $3.5B, Handshake has gained traction in a competitive market, although it has strong competition from recruiting giants LinkedIn and Indeed. It stands out, however, by helping students build new relationships and skills, rather than simply making connections to people they already know.
Steph
Company Specialist
Insights
Company
Funding (last 2 of 7 rounds)
Jan 2022
$200m
SERIES F
May 2021
$80m
SERIES E
Total funding: $434m
Company benefits
- 💰Equity and ownership in a fast-growing company
- 🍼16 Weeks of paid parental leave for birth giving parents & 10 weeks of paid parental leave for non-birth giving parents
- 💝Comprehensive medical, dental, and vision policies including LGTBQ+ Coverage. We also provide resources for Mental Health Assistance, Employee Assistance Programs and counseling support
- 💻Handshake offers $500/£360 home office stipend for you to spend during your first 3 months to create a productive and comfortable workspace at home
- 📚Generous learning & development opportunities and an annual $2,000/£1,500 stipend for you to grow your skills and career
- 🏦401k Match: Handshake offers a dollar-for-dollar match on 1% of deferred salary, up to a maximum of $1,200 per year
- 🏝 All full-time US-based Handshakers are eligible for our flexible time off policy to get out and see the world. In addition, we offer 8 standardized holidays, and 2 additional days of flexible holiday time off. Lastly, we have a Summer and Winter #ShakeBreak, two one-week periods of Collective Time Off
Company HQ
Financial District, San Francisco, CA
Articles
Leadership
Garrett Lord
(Co-Founder & CEO)Majored in Computer Science at Michigan Technological University. Interned at Palantir Technologies before co-founding Handshake in 2012.
Ben Christensen
(Co-Founder)Graduated from Michigan Technological University with a degree in Computer Networking & Systems Administration. Interned at Target and worked as a Developer at Up and Running Software. Was part of Arbor Networks' ASERT Security Research team.
Scott Ringwelski
(Co-Founder)Attained a degree in Computer Software Engineering from Michigan Technological University. Co-founded Handshake in 2012.
Share this job
View 27 more jobs at Handshake