Weekday, Inc. Logo

Weekday, Inc.

Software Engineer - Backend

Posted An Hour Ago
Be an Early Applicant
Remote
Hiring Remotely in United States
50-100 Hourly
Entry level
Remote
Hiring Remotely in United States
50-100 Hourly
Entry level
Create and evaluate repository-based backend coding tasks for advanced AI models. Responsibilities include designing debugging, feature, API, refactoring, and performance challenges; building reproducible environments and deterministic verifiers; developing reference solutions; evaluating task quality; and documenting requirements and verification criteria.
The summary above was generated by AI

This role is for one of our clients

Compensation: $50–$100 per hour

Engagement Type: Project-based contractor role, with payment per approved task

Time Commitment: Approximately 15 hours per week

Estimated Task Duration: Around 5 hours for trainers and 1.5 hours for reviewers

Work Arrangement: Fully remote

Technical Requirements: Hands-on expertise in at least one of Python, Java, Rust, Go, C++, or TypeScript

We are looking for experienced Backend Software Engineers to contribute to the development of Reinforcement Learning Environments (RLEs) designed to evaluate and improve the capabilities of advanced AI models in solving real-world software engineering challenges.

In this role, you will create complex, repository-based coding tasks that assess a model's ability to debug sophisticated issues, implement backend features, refactor existing systems, and optimize application performance. You will work with real codebases to define engineering problems, establish reproducible development environments, and develop reliable verification systems that evaluate submitted solutions.

The ideal candidate has strong backend engineering experience, excellent problem-solving abilities, and the technical depth to identify meaningful challenges within complex software systems. Prior experience in AI or machine learning is not mandatory.


RequirementsKey Responsibilities
  1. Design realistic and challenging backend engineering tasks using repositories and codebases with which you have hands-on experience.
  2. Develop problems involving complex bug fixes, backend feature implementation, API development, system refactoring, and performance optimization.
  3. Build reproducible environments that allow coding tasks to be executed and evaluated consistently.
  4. Create deterministic verifiers that identify correct solutions across different valid implementations while rejecting incomplete, incorrect, or hard-coded approaches.
  5. Develop reference solutions demonstrating effective approaches to solving each engineering challenge.
  6. Evaluate tasks for clarity, technical relevance, and verifiability, flagging ambiguous or unsuitable problems rather than submitting them.
  7. Document task requirements, technical assumptions, and verification criteria clearly.
Required Qualifications
  1. Strong hands-on backend development experience in at least one of the following programming languages: Python 3, Java, Rust, Go, C++, or TypeScript.
  2. Solid understanding of data structures, algorithms, software architecture, and core software engineering principles.
  3. Proven ability to debug complex backend systems, identify root causes, and implement reliable fixes.
  4. Experience developing backend features, working with large codebases, and improving application performance.
  5. Familiarity with code refactoring, legacy system modernization, and writing maintainable, scalable software.
  6. Ability to design reproducible test environments and develop reliable, deterministic verification mechanisms.
  7. Experience taking technical features or engineering solutions from problem definition through implementation and delivery.
  8. Strong written communication and documentation skills, with the ability to explain complex technical concepts clearly.
Preferred Skills
  • Experience building and maintaining backend services and APIs.
  • Understanding of distributed systems, system reliability, and performance optimization.
  • Familiarity with automated testing, debugging tools, and software verification techniques.
  • Experience working with open-source repositories or complex production codebases.
  • Interest in artificial intelligence and the technical challenges involved in evaluating advanced AI models.
Compensation Structure

This is an output-based engagement. Compensation ranges from $50 to $100 per hour, with payments made for tasks that meet the defined project specifications and receive approval. Actual time requirements may vary depending on task complexity, individual expertise, and workflow.

Availability and Joining Timeline

This is a flexible, project-based contractor opportunity requiring approximately 15 hours of availability per week. Candidates should be available to begin promptly. Selected professionals are expected to start their first tasks within 24–48 hours of completing the onboarding process.

Selection Process
  1. Submit your application and complete the screening questions.
  2. Participate in an AI-powered interview to demonstrate your technical expertise.
  3. Complete the profile review process.
  4. Finish onboarding with the Talent Operations team and get started on your first tasks.

Similar Jobs

20 Hours Ago
Easy Apply
Remote
United States
Easy Apply
115K-180K Annually
Entry level
115K-180K Annually
Entry level
Big Data • Fintech • Mobile • Payments • Financial Services
Develop backend systems and continuous delivery platforms that help engineering teams release software independently and safely. Responsibilities include writing tested and extensible code, collaborating with stakeholders, debugging code, participating in code reviews, balancing delivery speed with reliability, and contributing to team growth. The role involves working with distributed systems and technologies including Python or Kotlin, AWS, MySQL, and Kubernetes.
Top Skills: AWSCi/CdDistributed SystemsKotlinKubernetesMySQLPython
Yesterday
Easy Apply
Remote
United States
Easy Apply
173K-233K Annually
Senior level
173K-233K Annually
Senior level
Big Data • Fintech • Mobile • Payments • Financial Services
Own and deliver goals for ML training and serving infrastructure. Lead engineers through ambiguous, distributed-systems challenges; design, develop, and operate highly available backend platforms; monitor reliability and support on-call operations. Collaborate with product and engineering stakeholders, improve code and design standards, identify and resolve technical issues, and mentor team members. The role focuses on scalable systems that enable production model training and serving.
Top Skills: AWSKotlinKubernetesMySQLPython
Yesterday
Easy Apply
Remote
United States
Easy Apply
173K-233K Annually
Senior level
173K-233K Annually
Senior level
Big Data • Fintech • Mobile • Payments • Financial Services
Own and deliver quarterly engineering goals for Affirm’s ML Feature Platform. Design, develop, and launch scalable backend systems, lead engineers through ambiguous problems, collaborate with product and design stakeholders, improve platform reliability and availability, support on-call operations, establish quality standards, and mentor team members. The role focuses on highly available distributed systems supporting machine learning feature creation, storage, serving, and offline backfilling.
Top Skills: AWSKotlinKubernetesMySQLPython

What you need to know about the Boston Tech Scene

Boston is a powerhouse for technology innovation thanks to world-class research universities like MIT and Harvard and a robust pipeline of venture capital investment. Host to the first telephone call and one of the first general-purpose computers ever put into use, Boston is now a hub for biotechnology, robotics and artificial intelligence — though it’s also home to several B2B software giants. So it’s no surprise that the city consistently ranks among the greatest startup ecosystems in the world.

Key Facts About Boston Tech

  • Number of Tech Workers: 269,000; 9.4% of overall workforce (2024 CompTIA survey)
  • Major Tech Employers: Thermo Fisher Scientific, Toast, Klaviyo, HubSpot, DraftKings
  • Key Industries: Artificial intelligence, biotechnology, robotics, software, aerospace
  • Funding Landscape: $15.7 billion in venture capital funding in 2024 (Pitchbook)
  • Notable Investors: Summit Partners, Volition Capital, Bain Capital Ventures, MassVentures, Highland Capital Partners
  • Research Centers and Universities: MIT, Harvard University, Boston College, Tufts University, Boston University, Northeastern University, Smithsonian Astrophysical Observatory, National Bureau of Economic Research, Broad Institute, Lowell Center for Space Science & Technology, National Emerging Infectious Diseases Laboratories

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account