Lago

AI/ML Engineer | Talent Marketplace

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MidZdalniePart-time

#406674·Dodano dwa miesiące temu·32

Źródło: Lago

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Tech Stack / Keywords

AINetworkMachine LearningData ScienceNLP Computer VisionAlgorithmsMLOps

Podsumowanie oferty

The AI/ML Engineer role involves designing, building, and deploying machine learning models and AI systems that address real business problems. This position covers the full machine learning lifecycle from data preparation to production deployment and monitoring. The engineer collaborates closely with data engineers, product managers, and business stakeholders to deliver reliable and scalable AI solutions.

Wymagania

3–5 years of experience in machine learning engineering, data science, or related field.
Proficiency in Python and core ML libraries (scikit-learn, TensorFlow, PyTorch, or similar).
Strong understanding of machine learning fundamentals (supervised/unsupervised learning, model evaluation, feature engineering).
Experience deploying ML models to production environments (APIs, batch pipelines, or embedded systems).
Familiarity with data manipulation and analysis tools (Pandas, NumPy, SQL).
Solid software engineering practices including version control, testing, and code quality.
Strong analytical and problem-solving skills.

Nice to have:

Experience with LLMs, prompt engineering, and generative AI applications (OpenAI, Anthropic, LangChain, or similar).
Familiarity with MLOps platforms (MLflow, Weights & Biases, SageMaker, Vertex AI, or similar).
Experience with cloud ML infrastructure (AWS, GCP, or Azure AI/ML services).
Knowledge of data engineering tools and pipelines (Spark, Airflow, dbt, or similar).
Experience with NLP techniques (transformers, embeddings, RAG pipelines).
Advanced degree (M.S. or Ph.D.) in Computer Science, Statistics, or related field.

Obowiązki

Design, develop, and deploy machine learning models for classification, regression, NLP, computer vision, recommendation, or other use cases.
Work with data engineers to build and maintain data pipelines for ML model training and inference.
Evaluate and select appropriate algorithms, frameworks, and architectures.
Train, validate, and fine-tune models using best practices to avoid overfitting.
Deploy models to production and build robust inference pipelines.
Monitor model performance post-deployment and implement retraining and drift detection strategies.
Collaborate with product and engineering teams to integrate AI features into applications.
Conduct experiments, document findings, and present insights to stakeholders.
Stay updated on AI/ML research and assess business applicability.
Contribute to MLOps practices, tooling, and infrastructure.

Benefity

Become a Certified Professional through the HireLago vetting process.
Showcase your profile on the HireLago Talent Marketplace, trusted by startups, agencies, and companies worldwide.
Gain access to exclusive remote opportunities before public advertisement.
Get matched with roles fitting your skills, experience, schedule, and salary expectations.
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