Description review
#991 - Machine Learning Engineer
Venon Solutions · United States · back to the listing
HR standards
53/100
needs work
Title ↔ description
84/100
solid
Reads as
Machine Learning Engineer
100% 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
- 22 bullet points. Long requirement lists deter qualified candidates, who read them as hard gates. Scope clarity
- 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 Opportunity only available for professionals located in Latin America.
The client is a consulting company dedicated to the application of innovative AI for business transformation. They partner with organizations to enable their AI adoption journey through the service and expertise of their integrated business and AI Lab. With Enterprise AI adoption as their core, the team brings deep expertise in full stack software development, AI/ML engineering, cloud architecture, data analytics, and support operations.
Requirements:
• Native Spanish or Portuguese language.
•
Advanced English level (B2/C1) to ensure fluent communication across teams.
• 5+ years building and shipping production ML/data systems in Python - services owned through deploy, monitoring, and incident response.
• Practical experience with LLMs, embedding models, and retrieval-augmented generation (RAG), including prompt engineering and fine-tuning where appropriate.
• Experience deploying and operating ML solutions in production on Azure and/or AWS, with MLOps practices for versioning, monitoring, and retraining.
•
Production-grade software engineering: PyTest, CI gating, schema migrations, API design (FastAPI), PostgreSQL.
• Demonstrated ability to generalise a system across multiple problem domains rather than special-casing each - having built a platform.
• Excellent client-facing communication, presentation, and workshop facilitation skills.
Responsibilities:
• Own, manage, enhance, and support the client's decision-intelligence platform as the foundation of AI/ML delivery.
• Own model selection, feature engineering, and evaluation strategy across client engagements.
• Frame business problems as ML problems, defining success metrics, data requirements, and validation approaches.
• Design, build, deploy, monitor, and support ML and AI services in production - from data ingestion through to modelling, API, and dashboard validation.
• Generalise solutions across problem domains rather than building one-off implementations.
• Integrate LLM and RAG capabilities where they add value, applying prompt engineering and fine-tuning as required.
• Implement MLOps practices for model versioning, monitoring, retraining, and performance management.
What do we offer?
• Competitive salary in USD.
•
100% Remote work.
•
Duration: Long-term.
•
Type of contract: Independent Contractor with Venon Solutions LLC.
•
Paid Time Off: 2 weeks / 10 business days.
•
Paid Holidays from the US calendar.
• Working hours: Full-time EST, fully committed.
Originally posted on Himalayas
The client is a consulting company dedicated to the application of innovative AI for business transformation. They partner with organizations to enable their AI adoption journey through the service and expertise of their integrated business and AI Lab. With Enterprise AI adoption as their core, the team brings deep expertise in full stack software development, AI/ML engineering, cloud architecture, data analytics, and support operations.
Requirements:
• Native Spanish or Portuguese language.
•
Advanced English level (B2/C1) to ensure fluent communication across teams.
• 5+ years building and shipping production ML/data systems in Python - services owned through deploy, monitoring, and incident response.
• Practical experience with LLMs, embedding models, and retrieval-augmented generation (RAG), including prompt engineering and fine-tuning where appropriate.
• Experience deploying and operating ML solutions in production on Azure and/or AWS, with MLOps practices for versioning, monitoring, and retraining.
•
Production-grade software engineering: PyTest, CI gating, schema migrations, API design (FastAPI), PostgreSQL.
• Demonstrated ability to generalise a system across multiple problem domains rather than special-casing each - having built a platform.
• Excellent client-facing communication, presentation, and workshop facilitation skills.
Responsibilities:
• Own, manage, enhance, and support the client's decision-intelligence platform as the foundation of AI/ML delivery.
• Own model selection, feature engineering, and evaluation strategy across client engagements.
• Frame business problems as ML problems, defining success metrics, data requirements, and validation approaches.
• Design, build, deploy, monitor, and support ML and AI services in production - from data ingestion through to modelling, API, and dashboard validation.
• Generalise solutions across problem domains rather than building one-off implementations.
• Integrate LLM and RAG capabilities where they add value, applying prompt engineering and fine-tuning as required.
• Implement MLOps practices for model versioning, monitoring, retraining, and performance management.
What do we offer?
• Competitive salary in USD.
•
100% Remote work.
•
Duration: Long-term.
•
Type of contract: Independent Contractor with Venon Solutions LLC.
•
Paid Time Off: 2 weeks / 10 business days.
•
Paid Holidays from the US calendar.
• Working hours: Full-time EST, fully committed.
Originally posted on Himalayas