Description review
Test - AI and Data Engineer
PowerData Group Consulting · United States · back to the listing
HR standards
58/100
needs work
Title ↔ description
55/100
needs work
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
- 39 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.
This is a remote position.
AI Engineer
SummaryWe are looking for a talented AI Engineer to create, refine, and deploy advanced AI-driven solutions that solve genuine business problems. This role involves leveraging cutting-edge technologies, including machine learning, Large Language Models (LLMs), and automation tools, to construct robust and secure applications. The successful applicant will combine strong coding abilities with hands-on experience in AI development to effectively convert business needs into functional technical systems.
Responsibilities
• Create, test, and launch AI and machine learning systems.
• Build and connect applications utilizing generative AI, LLMs, and various AI APIs.
• Develop intelligent automation workflows, chatbots, and AI agents.
• Deploy Retrieval-Augmented Generation (RAG) systems and link AI models with organizational knowledge bases and databases.
• Design and sustain backend services and APIs for AI-driven applications.
• Process both structured and unstructured data to facilitate model training and assessment.
• Assess the reliability, scalability, accuracy, and performance of AI models.
• Apply prompt engineering strategies, optimize models, and utilize evaluation methods.
• Uphold data governance, privacy standards, responsible AI principles, and security protocols.
• Partner with business analysts, developers, product managers, and other key stakeholders.
• Track the performance of live AI solutions and drive continuous improvements.
Requirements
Requirements:
•
Essential Qualifications:
• Bachelor's degree in Software Engineering, Data Science, Artificial Intelligence, Computer Science, or a comparable discipline, or proven equivalent experience.
• Proficiency in Python programming.
• Solid grasp of deep learning, machine learning, and core AI principles.
• Hands-on experience with generative AI and LLM technologies.
• Familiarity with libraries and frameworks like scikit-learn, TensorFlow, or PyTorch.
• Proven track record of integrating AI models via APIs (e.g., Anthropic, OpenAI, or similar providers).
• Competence in backend development, JSON, and REST APIs.
• Experience managing both SQL and NoSQL databases.
• Understanding of AI output validation, model evaluation, and prompt engineering.
• Knowledge of software development standards, testing, version control (Git), and related tools.
• Excellent communication, problem-solving, and analytical capabilities.
•
Preferred Qualifications:
• Background in creating multi-step AI workflows and AI agents.
• Familiarity with semantic search, vector databases, and RAG architectures.
• Experience using tools like LlamaIndex, LangChain, or comparable platforms.
• Knowledge of cloud environments including Google Cloud, Microsoft Azure, or AWS.
• Proficiency with Docker, CI/CD pipelines, and production deployment processes.
• Insight into AI evaluation frameworks, model monitoring, and MLOps.
• Understanding of responsible AI, privacy regulations, and cybersecurity.
• Experience embedding AI into enterprise systems such as recruitment tools, ERP, or CRM.
•
Core Competencies:
• Exceptional analytical and technical proficiency.
• Capacity to resolve intricate issues and deliver actionable solutions.
• Flexibility to collaborate effectively and work autonomously.
• Superior written and oral communication skills.
• Commitment to staying current with the fast-paced AI landscape.
• Skill in translating complex technical details for non-technical audiences.
Benefits
AI Data Remote
Originally posted on Himalayas
AI Engineer
SummaryWe are looking for a talented AI Engineer to create, refine, and deploy advanced AI-driven solutions that solve genuine business problems. This role involves leveraging cutting-edge technologies, including machine learning, Large Language Models (LLMs), and automation tools, to construct robust and secure applications. The successful applicant will combine strong coding abilities with hands-on experience in AI development to effectively convert business needs into functional technical systems.
Responsibilities
• Create, test, and launch AI and machine learning systems.
• Build and connect applications utilizing generative AI, LLMs, and various AI APIs.
• Develop intelligent automation workflows, chatbots, and AI agents.
• Deploy Retrieval-Augmented Generation (RAG) systems and link AI models with organizational knowledge bases and databases.
• Design and sustain backend services and APIs for AI-driven applications.
• Process both structured and unstructured data to facilitate model training and assessment.
• Assess the reliability, scalability, accuracy, and performance of AI models.
• Apply prompt engineering strategies, optimize models, and utilize evaluation methods.
• Uphold data governance, privacy standards, responsible AI principles, and security protocols.
• Partner with business analysts, developers, product managers, and other key stakeholders.
• Track the performance of live AI solutions and drive continuous improvements.
Requirements
Requirements:
•
Essential Qualifications:
• Bachelor's degree in Software Engineering, Data Science, Artificial Intelligence, Computer Science, or a comparable discipline, or proven equivalent experience.
• Proficiency in Python programming.
• Solid grasp of deep learning, machine learning, and core AI principles.
• Hands-on experience with generative AI and LLM technologies.
• Familiarity with libraries and frameworks like scikit-learn, TensorFlow, or PyTorch.
• Proven track record of integrating AI models via APIs (e.g., Anthropic, OpenAI, or similar providers).
• Competence in backend development, JSON, and REST APIs.
• Experience managing both SQL and NoSQL databases.
• Understanding of AI output validation, model evaluation, and prompt engineering.
• Knowledge of software development standards, testing, version control (Git), and related tools.
• Excellent communication, problem-solving, and analytical capabilities.
•
Preferred Qualifications:
• Background in creating multi-step AI workflows and AI agents.
• Familiarity with semantic search, vector databases, and RAG architectures.
• Experience using tools like LlamaIndex, LangChain, or comparable platforms.
• Knowledge of cloud environments including Google Cloud, Microsoft Azure, or AWS.
• Proficiency with Docker, CI/CD pipelines, and production deployment processes.
• Insight into AI evaluation frameworks, model monitoring, and MLOps.
• Understanding of responsible AI, privacy regulations, and cybersecurity.
• Experience embedding AI into enterprise systems such as recruitment tools, ERP, or CRM.
•
Core Competencies:
• Exceptional analytical and technical proficiency.
• Capacity to resolve intricate issues and deliver actionable solutions.
• Flexibility to collaborate effectively and work autonomously.
• Superior written and oral communication skills.
• Commitment to staying current with the fast-paced AI landscape.
• Skill in translating complex technical details for non-technical audiences.
Benefits
AI Data Remote
Originally posted on Himalayas