Machine Learning Engineer

Company Overview

Company details are not specified.

Job Summary

The Machine Learning Engineer will be responsible for designing, developing, and implementing machine learning models and algorithms, primarily for Natural Language Processing (NLP) projects. The role expects candidates to leverage their programming skills and cloud experience to build data pipelines, optimize models, and ensure the integration of these systems into business intelligence and analytics frameworks.

Responsibilities

• Develop and implement machine learning models and data pipelines from end to end.
• Manage and orchestrate environments using tools like Docker and cloud platforms (GCP preferred).
• Conduct data engineering and feature engineering to prepare datasets for machine learning tasks.
• Monitor and evaluate machine learning models using advanced metrics; refine models based on performance.
• Collaborate on API development, utilizing frameworks such as FastAPI.
• Optimize processing and deployment pipelines for large-scale data applications using technologies like CI/CD.

Qualifications

• Programming Languages: Strong proficiency in Python and Java.
• Cloud Experience: Hands-on experience with Google Cloud Platform (GCP) and its services.
• Orchestration Tools: Familiarity with orchestrators like Vertex AI pipelines and Apache Airflow.
• Machine Learning Knowledge: Understanding of the entire machine learning cycle, especially for NLP projects.
• Data Engineering Skills: Experience in data and feature engineering techniques.
• ML Frameworks: Knowledge of frameworks such as TensorFlow and PyTorch.
• SQL Proficiency: Advanced knowledge of SQL.
• API Development: Experience in developing APIs, preferably with FastAPI.

Preferred Skills

• Experience with hyperparameter tuning.
• Proficiency in Apache Spark, Apache Beam, or Apache Flink.
• Hands-on experience with distributed computing.
• Understanding of data architecture design.
• Familiarity with Kubernetes and vector-based databases like Qdrant.
• Experience with large language models (LLM) and embedding techniques.

Experience

Details regarding minimum experience required are not specified; experience in relevant technologies and projects is essential.

Environment

The typical work setting, location, or whether the role is remote, in-office, or hybrid is not specified.

Salary

Salary details are not provided.

Growth Opportunities

Opportunities for advancement within the company are not specified.

Benefits

Details on offered benefits, including insurance and paid leave, are not provided.