ml engineer for scalable AI solutions

HireHi; United States; Remote; USD 120,000 - 180,000; Full time

Benefits offered by this job

Annual bonus

Private health insurance

Relocation assistance

Career growth opportunities

Mentoring and onboarding

Training portal access

Certification support

Referral program

English courses

Corporate events

Snacks and beverages

Job summary

Andersen ищет ML-инженера для разработки и поддержки ML-решений в рамках полного цикла: проектирование, обучение и развёртывание моделей.

Вы будете строить конвейеры данных, сотрудничать с аналитиками, обеспечивать качество данных и мониторинг моделей, работая с AWS SageMaker, TensorFlow/PyTorch и Docker.

Компания предлагает наставничество, возможности карьерного роста, программы сертификации и доступ к обучающим ресурсам.

Qualifications

• 2+ года опыта в роли Machine Learning Engineer или аналогичной.
• Python, включая scikit-learn, pandas, NumPy и matplotlib.
• Понимание регрессии, классификации, кластеризации, валидации моделей и метрик.
• Опыт TensorFlow, PyTorch или Keras.
• Опыт работы с AWS SageMaker.
• Знакомство с AWS Bedrock, foundation models, генеративными моделями, fine-tuning и LLM-оркестрацией.
• Опыт подготовки данных, инженерии признаков и оценки моделей.
• Знание SQL и работа с структурированными и полуструктурированными наборами данных.
• Понимание развёртывания через REST API, FastAPI, Flask, Docker и контейнеризацию.
• Навыки MLOps: пайплайны, версионирование моделей, мониторинг, воспроизводимость.
• Git и другие системы контроля версий.
• Сильные аналитические способности, коммуникация и решение проблем.
• Готовность учиться новым ML-методикам и облачным инструментам.

Responsibilities

• Проектирование, обучение и оценка ML-моделей (supervised, unsupervised, NLP).
• Построение масштабируемых ML-пайплайнов и данных.
• Сотрудничество с аналитиками для подготовки обучающих наборов.
• Развертывание моделей в продакшн для пакетного или реального времени инференса.
• Мониторинг качества данных и производительности моделей.
• Оптимизация моделей по скорости, интерпретируемости и затратам.
• Документация ML-рабочих процессов и обеспечение воспроизводимости.

Skills

ML Experience

Python

scikit-learn

pandas

NumPy

matplotlib

Regression

Classification

Clustering

Model validation

Performance metrics

TensorFlow

PyTorch

Keras

SageMaker

AWS Bedrock

Foundation models

Generative models

Fine-tuning

LLM orchestration

Data preprocessing

Feature engineering

Model evaluation

SQL

REST APIs

FastAPI

Flask

Docker

Containerization

MLOps

Pipeline automation

Model versioning

Monitoring

Reproducibility

Git

Analytical thinking

Communication

Problem-solving

Continuous learning

Tools

Git

Job description

Описание: Andersen is a pre-IPO software development company providing full-cycle services. It helps enterprises and middle-sized firms worldwide transform their businesses by creating digital solutions with innovative technologies.

Задачи

• Design, train, and evaluate machine learning models, including supervised, unsupervised, and NLP models
• Build scalable data and ML pipelines using modern tools
• Collaborate with subject matter experts and analysts to prepare training datasets
• Deploy models to production for batch or real-time inference
• Monitor and maintain model performance and data quality
• Optimize models for performance, interpretability, and cost
• Document ML workflows and ensure reproducibility.

Требования

• 2+ Years of experience as a Machine Learning Engineer or in a similar role
• Proficiency in Python, including hands-on experience with scikit-learn, pandas, NumPy, and matplotlib
• Strong understanding of regression, classification, clustering, model validation, and performance metrics
• Practical experience with TensorFlow, PyTorch, or Keras
• Proven experience building, training, and deploying ML models using AWS SageMaker
• Familiarity with AWS Bedrock, foundation models, generative models, fine-tuning, and LLM orchestration
• Hands-on experience with data preprocessing, feature engineering, and model evaluation
• Knowledge of SQL and experience with structured and semi-structured datasets
• Understanding of ML model deployment with REST APIs, FastAPI, Flask, Docker, and containerization
• Exposure to MLOps practices, including pipeline automation, model versioning, monitoring, and reproducibility
• Familiarity with Git and other version control systems
• Strong analytical thinking, communication, and problem-solving skills
• Willingness to stay current with emerging ML techniques, frameworks, and cloud AI tools
• English at Upper-Intermediate level or above; German at Intermediate+ level or above.

Условия

• Up to an additional 1,000 USD per month depending on expertise, included in the annual bonus
• Professional, financial, and career growth opportunities
• Mentoring and onboarding systems for each new employee
• Access to the corporate training portal
• Certification compensation for AWS, PMP, and other certifications
• Referral program
• English courses
• Private health insurance and sports activity compensation
• Corporate events, pizza days, PlayStation, fruits, coffee, snacks, and movies
• Relocation is available across listed EU locations.