Description review
Senior Software Engineer
micro1 · Remote · back to the listing
HR standards
72/100
solid
Title ↔ description
41/100
poor
Reads as
Machine Learning Engineer
81% confident
What this role officially is
data scientist — ESCO, the EU occupation classification
Data scientists find and interpret rich data sources, manage large amounts of data, merge data sources, ensure consistency of data-sets, and create visualisations to aid in understanding data. They build mathematical models using data, present and communicate data insights and findings to specialists and scientists in their team and if required, to a non-expert audience, and recommend ways to apply the data.
Also known as: data scientists, data engineer, research data scientist, data expert, data research scientist
How others title the same work
Large employers
- Applied AI Engineer Automattic
- Machine Learning Engineer, CX Intelligence Coinbase
- AI Engineer - FDE (Forward Deployed Engineer) Databricks
- AI Engineer - FDE (Forward Deployed Engineer) - U.S. Federal Sector Databricks
- Senior AI Engineer – Notebooks Datadog
Startups
- Attendi | Medior Machine Learning Engineer | Amsterdam, Netherlands | ONSITE (hybrid) | €6,000 - €7,000 per month | Full-time (80–100%, ~4–5 days/week) | Visa sponsorship + 30% ruling possible Attendi
- Member of Technical Staff (applied) Anthrogen
- Aptura AI | Full-Time | MTS (Applied AI), MTS (SWE / Product) | London | ONSITE / HYBRID Aptura AI
- Arcforma AI (arcforma.ai) | AI Engineer (Marketing / Construction / Arcforma AI (arcforma.ai)
- Staff AI Engineer - Agent Architecture & Behavior Artisan
What the listing never says
- No pay range published. Candidates cannot tell whether applying is worth their time. Pay transparency
The listing, marked up
Nothing in the wording of this listing tripped a check. The scores above still judge how complete and coherent it is.
Job Title: Senior Software Engineer
Job Type: Contractor (~15 hrs a week)
Location: Remote (Globally)
Job Summary: In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input. No prior experience in AI is required — your domain knowledge is what matters.
As an expert you will be creating Reinforcement Learning Environments which test an AI model's ability to solve complex software engineering workflows. These workflows are similar in scope to common DevOps | CI/CD | Debugging workflows using common cli tools such as git, docker, gdb, asan, ffmpeg and many more. Your task will be to create reproducible rl environments that test a model's ability to solve these workflows along with a golden reference solution.
Required Skills and Qualifications:
• Proficiency in C++, Python, JAVA, GoLang, Typescript, or Rust.
• Deep understanding of algorithms, data structures, and performance tuning.
• Demonstrated experience in debugging complex software issues and delivering maintainable solutions.
• Strong background in feature development and codebase refactoring.
• Proven ability to optimize software for performance and scalability.
• Exceptional written and verbal communication skills, with a keen attention to detail.
• Track record of success in collaborative, cross-functional teams, ideally in remote settings.
Preferred Qualifications:
• Previous experience working on large-scale, distributed codebases.
• Familiarity with modern AI or machine learning systems is a plus, though not required.
• Background in participating in rigorous code reviews and contributing to the development of software best practices.
Process:
• Apply to the role, filling out the screening questions
• Complete AI interview (aprox. 30 minutes)
• Technical Assessment (Tentative)
• Hiring Manager review
Compensation Structure
Compensation is output-based; experts are paid per task that meets the project specifications. The time required to complete work may vary depending on the expert’s experience and workflow. Minimum submission requirements apply. Experts must submit a minimum of tasks per week.
Start Timeline & Availability
We typically fill roles within 48 hours and are looking for experts ready to jump in right away. If selected, we expect you to start your first tasks within 24–48 hours of completing onboarding.
Originally posted on Himalayas
Job Type: Contractor (~15 hrs a week)
Location: Remote (Globally)
Job Summary: In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input. No prior experience in AI is required — your domain knowledge is what matters.
As an expert you will be creating Reinforcement Learning Environments which test an AI model's ability to solve complex software engineering workflows. These workflows are similar in scope to common DevOps | CI/CD | Debugging workflows using common cli tools such as git, docker, gdb, asan, ffmpeg and many more. Your task will be to create reproducible rl environments that test a model's ability to solve these workflows along with a golden reference solution.
Required Skills and Qualifications:
• Proficiency in C++, Python, JAVA, GoLang, Typescript, or Rust.
• Deep understanding of algorithms, data structures, and performance tuning.
• Demonstrated experience in debugging complex software issues and delivering maintainable solutions.
• Strong background in feature development and codebase refactoring.
• Proven ability to optimize software for performance and scalability.
• Exceptional written and verbal communication skills, with a keen attention to detail.
• Track record of success in collaborative, cross-functional teams, ideally in remote settings.
Preferred Qualifications:
• Previous experience working on large-scale, distributed codebases.
• Familiarity with modern AI or machine learning systems is a plus, though not required.
• Background in participating in rigorous code reviews and contributing to the development of software best practices.
Process:
• Apply to the role, filling out the screening questions
• Complete AI interview (aprox. 30 minutes)
• Technical Assessment (Tentative)
• Hiring Manager review
Compensation Structure
Compensation is output-based; experts are paid per task that meets the project specifications. The time required to complete work may vary depending on the expert’s experience and workflow. Minimum submission requirements apply. Experts must submit a minimum of tasks per week.
Start Timeline & Availability
We typically fill roles within 48 hours and are looking for experts ready to jump in right away. If selected, we expect you to start your first tasks within 24–48 hours of completing onboarding.
Originally posted on Himalayas