Job Description

Contract Type: EoR, Contract or Salaried Subcontractor, depending on the country

YoE: 5+

Start Date: Asap (within 30 days)

Engagement Length: 12-18 months max, depending on the country

Special reqs: Experience working on the backends of large (10mil+ daily active users) B2C applications, product engineering experience

Vetting:

Round 1: 60 minutes Live Coding Round with Barraiser (Python, Golang, Kafka)

Round 2: 15 minutes Turing Chat

Round 3: 45 minutes client Hiring Manager Interview

Round 4-5: Client Technical Rounds

Skills: Golang, Python, Kafka

About Client

Our Clinet is one of the world's fastest-growing AI companies accelerating the advancement and deployment of powerful AI systems.

They helps customers in two ways: Working with the world's leading AI labs to advance frontier model capabilities in thinking, reasoning, coding, agentic behavior, multimodality, multilinguality, STEM and frontier knowledge; and leveraging that work to build real-world AI systems that solve mission-critical priorities for companies.

Powering this growth is Turing's talent cloud--an AI-vetted pool of 4M+ software engineers, data scientists, and STEM experts who can train models and build AI applications. All of this is orchestrated by ALAN--our AI-powered platform for matching and managing talent, and generating high-quality human and synthetic data to improve model performance. ALAN also accelerates workflows for model and agent evals, supervised fine-tuning, reinforcement learning, reinforcement learning with human feedback, preference-pair generation, benchmarking, data capture for pre-training, post-training, and building AI applications.

Turing--based in San Francisco, California--was named #1 on The Information's annual list of "Top 50 Most Promising B2B Companies," and has been profiled by Fast Company, TechCrunch, Reuters, Semafor, VentureBeat, Entrepreneur, CNBC, Forbes, and many others. Turing's leadership team includes AI technologists from Meta, Google, Microsoft, Apple, Amazon, X, Stanford, Caltech, and MIT.

About the Team

The ML Ranking Platform team builds and runs the services that coordinate contextualized and personalized rankings. We build ML infrastructure, including a scatter-gather ranking coordination service and feature indexes. We work closely with a team of MLEs to develop and productionize new models and with a team of ML backend engineers that build inference and training services and feature stores.

Ranking is a core and growing part of our platform, and connecting users with the content they're looking for is key to the future. This is particularly salient right now, as our society is currently engaging in a deep discussion around the algorithms used to match users with content. Our team is acutely aware of this. Our team mantra is "Intention over Attention". We are deeply concerned with helping our users fulfill their intention for visiting, not just capturing their attention.

Key Responsibilities

System design. This requires a good understanding of how the systems work, with particular focus on latency and scalability. Development. RP works mainly with Go and some Python. Skills in testing, SOLID and design patterns are a must. Systems architecture. RP makes extensive use of Kubernetes, Kafka, Redis and Postgres, and many internal and third party APIs, with focus on resilience, monitoring and alerting, and automation.
Qualifications for this role:

Proficiency in Python and Go, object oriented programming, design patterns. Proficiency in testing. Ability to naturally write clear, unconvoluted, testable code. Experience with Kubernetes, Kafka, Redis (user level). Experience with AWS and/or Google Cloud (user level).
Bonus points

Experience with highly scalable systems. Experience with Terraform. Experience with ML systems or frontend (React) are a big bonus!
Job Type: Fixed term contract
Contract length: 12 months

Base Pay: 17.85-50.31 per hour

Expected hours: 40 per week

Benefits:

Work from home
Experience:

Back-end development: 5 years (required) Python: 5 years (required) Go: 3 years (required) Kafka: 3 years (required)
Work Location: Remote