AI engineer in data platforms

Intellias; United States; Remote; USD 140,000 - 200,000; Full time

Job summary

Intellias ищет опытного инженера ML для ведения проектов по созданию и внедрению AI-решений в глобальном масштабе. Вы будете разрабатывать и внедрять ML и AI системы, включая CV, NLP и Generative AI, работая с кросс-функциональными командами.

Требуется академическое образование, сильная грамотность в Python и ML-стеке, а также опыт развёртываний в облаках. Вы будете наставлять коллег и участвовать в формировании технической дорожной карты компании.

Qualifications

• 5+ лет практического опыта в машинном обучении, AI-исследованиях или data science.
• Магистр или PhD в CS, Data Science, ML или смежной области.
• Сильная экспертиза в CV, NLP и Generative AI.
• Опыт разработки production ML систем и LLM-приложений, включая RAG и семантический поиск.
• Глубокие знания PyTorch, TensorFlow, NumPy, Pandas, scikit-learn.
• Опыт развёртывания в облаках (AWS/Azure/GCP) и контейнеризации.
• Опыт работы с LangChain, LlamaIndex, Haystack или эквивалентами.
• Навыки оценки и мониторинга моделей, безопасность и ответственность AI.
• Хорошие коммуникативные навыки и умение объяснять сложные концепции.
• Плюсом: MLOps, multimodal, LoRA/PEFT, вклад в open-source.

Responsibilities

• Ведущая идея, дизайн и реализация AI Proof-of-Concepts и систем ML от исследования до продакшна.
• Разработка ML/AI систем в CV, NLP и Generative AI.
• Кросс-функциональное сотрудничество с инженерами, PM и бизнес-стейкхолдерами.
• Архитектура и поддержка production-grade AI систем на всем жизненном цикле.
• Проектирование RAG-пайплайнов, семантического поиска и многоагентных рабочих процессов.
• Разработка фреймфорков оценки ML/AI систем и мониторинга.
• Оптимизация систем по масштабируемости, задержке и затратам.
• Наставничество младших ML-инженеров и специалистов по данным.
• Следить за исследованиями и инструментами в AI.

Skills

Python

ML инженерия

Computer Vision

NLP

Generative AI

LLM-приложения

RAG пайплайны

Облачные развёртывания

Оценка моделей

Коммуникации

Education

Master's degree in CS/DS/ML

PhD in CS/DS/ML

Tools

PyTorch

TensorFlow

Hugging Face

NumPy

Pandas

scikit-learn

LangChain

LlamaIndex

Haystack

DSPy

MLflow

Airflow

Terraform

CI/CD

Job description

Описание:

Over 20 years of market experience, Intellias brings together technologists, creators and innovators in Europe, North and Latin America, and the Middle East. Join our international team and take the mission to solve the advanced tech challenges of tomorrow!

Задачи:

Lead the ideation, design, and execution of AI proofs-of-concept and end-to-end machine learning systems, from research and experimentation through to scalable production deployment. Develop and implement machine learning and AI systems across domains including Computer Vision, NLP, and Generative AI, solving complex business and product challenges. Collaborate cross-functionally with engineering, product management, and business stakeholders to translate business objectives into scalable AI-driven capabilities and production-ready solutions. Architect and maintain production-grade AI systems across the full lifecycle, including data ingestion, feature engineering, model training, retrieval pipelines, orchestration layers, deployment, evaluation, and monitoring. Design and implement Retrieval-Augmented Generation (RAG) pipelines, semantic search systems, and multi-agent workflows, selecting appropriate architectures based on performance, latency, cost, and compliance constraints. Design evaluation frameworks for machine learning and generative AI systems, including offline evaluation, human-in-the-loop validation, automated scoring, and production monitoring. Optimize AI systems for scalability, latency, and cost efficiency, including batching, caching, quantization, and model selection strategies. Design and apply advanced mathematical models and statistical methods to analyze large, multi-modal datasets, including time series, classification, regression, and representation learning tasks. Collaborate on AI architecture decisions and contribute to technical roadmap planning, identifying high-impact opportunities for AI adoption across the organization. Mentor and provide technical guidance to junior ML engineers and data scientists, promoting engineering best practices and a culture of continuous learning. Stay current with emerging research, tools, and architectures in AI and machine learning, proactively evaluating and introducing relevant advancements.

Требования:

5+ years of hands-on experience in machine learning, AI research, or data science, with a proven track record of delivering production-grade ML solutions. Masters or Ph.D. in Computer Science, Data Science, Machine Learning, or a related quantitative field. Strong expertise across core ML disciplines including supervised and unsupervised learning, time series modeling, classification, regression, and model evaluation. Deep hands-on experience developing production systems in Computer Vision, NLP, and Generative AI. Strong experience building LLM-based applications, including RAG pipelines, agentic workflows, semantic search, and tool-using AI systems. Experience designing evaluation frameworks for generative AI systems, including prompt evaluation, hallucination detection, and performance monitoring. Proficiency in Python and modern ML ecosystem including PyTorch, TensorFlow, Hugging Face, NumPy, Pandas, and scikit-learn. Experience with modern LLM orchestration and serving frameworks such as LangChain, LlamaIndex, DSPy, Haystack, or equivalent. Experience deploying and scaling AI systems on cloud platforms (AWS, Azure, or GCP), including managed ML services and containerized deployments. Experience building and maintaining end-to-end ML pipelines, including data processing, model training, deployment, and monitoring. Understanding of responsible AI principles, including bias mitigation, safety guardrails, and governance considerations. Proficiency with version control (Git) and software engineering best practices for collaborative ML development. Excellent communication skills, with the ability to convey complex technical concepts to both technical and non-technical stakeholders. Будет плюсом: Experience with MLOps tooling and workflows, including MLflow, Apache Airflow, Terraform, and CI/CD pipelines for model deployment; Experience with model serving and inference optimization tools such as vLLM; Experience working with feature stores, real-time data pipelines, or streaming AI systems; Experience with distributed training or large-scale model training frameworks; Experience with multimodal AI systems (vision-language models, audio-text, document AI); Experience with fine-tuning large language models or parameter-efficient training techniques (LoRA, PEFT, etc.); Experience contributing to open-source ML projects or publications in peer-reviewed venues; An Associate, Professional or Specialty-level certification from one of our strategic technology partners - AWS, Microsoft, Google, Databricks or Anthropic - aligned with your tech stack

Условия:

At Intellias, where technology takes center stage, people always come before processes. By creating a comfortable atmosphere in our team, we empower individuals to unlock their true potential and achieve extraordinary results. That's why we offer a range of benefits that support your well-being and charge your professional growth.