Senior ML Engineer

Aimlroles; Vermont; On-site; USD 100,000 - 160,000; Full time

Job summary

Aimlroles is seeking a machine learning engineer to develop models, preprocess data, and deploy solutions in production. You will collaborate with data scientists and software engineers to implement scalable ML systems and continuously improve model performance.

The role requires 2–5 years of ML experience, proficiency in Python/Java/Scala, and strong communication skills. Familiarity with GCP, ML frameworks, and Git is essential.

Qualifications

• Bachelor's degree or higher in Computer Science, Engineering, Mathematics, or a related field.
• 2–5 years of experience in machine learning, data science, or a related field.
• Proficiency in programming languages such as Python, Java, or Scala.
• Experience with machine learning frameworks and libraries such as TensorFlow, PyTorch, or scikit-learn.
• Strong understanding of machine learning algorithms and techniques, including supervised and unsupervised learning, deep learning, and reinforcement learning.
• Experience with cloud platforms such as Google Cloud Platform (GCP), including services like BigQuery, Cloud Storage, and AI Platform.
• GCP Professional Machine Learning Engineer certification is required.
• Experience with version control systems such as Git.
• Excellent problem-solving skills and attention to detail.
• Strong communication and collaboration skills.

Responsibilities

• Develop machine learning models and algorithms to address business needs.
• Collaborate with data scientists and software engineers to design and implement scalable and efficient solutions.
• Clean, preprocess, and analyze large datasets to extract meaningful insights.
• Deploy machine learning models into production environments and monitor their performance.
• Continuously improve model accuracy and performance through experimentation and optimization.
• Stay up-to-date with the latest advancements in machine learning and related technologies.
• Communicate findings and results to stakeholders in a clear and concise manner.

Education

Bachelor's degree or higher in Computer Science, Engineering, Mathematics, or a related field

2–5 years of experience in machine learning, data science, or a related field

Excellent problem-solving skills

Strong communication and collaboration skills

Tools

Python

Java

Scala

TensorFlow

PyTorch

scikit-learn

Google Cloud Platform (GCP)

BigQuery

Cloud Storage

AI Platform

Git

Job description

Responsibilities

• Develop machine learning models and algorithms to address business needs.
• Collaborate with data scientists and software engineers to design and implement scalable and efficient solutions.
• Clean, preprocess, and analyze large datasets to extract meaningful insights.
• Deploy machine learning models into production environments and monitor their performance.
• Continuously improve model accuracy and performance through experimentation and optimization.
• Stay up-to-date with the latest advancements in machine learning and related technologies.
• Communicate findings and results to stakeholders in a clear and concise manner.

Requirements

• Bachelor's degree or higher in Computer Science, Engineering, Mathematics, or a related field.
• 2~5 years of experience in machine learning, data science, or a related field.
• Proficiency in programming languages such as Python, Java, or Scala.
• Experience with machine learning frameworks and libraries such as TensorFlow, PyTorch, or scikit-learn.
• Strong understanding of machine learning algorithms and techniques, including supervised and unsupervised learning, deep learning, and reinforcement learning.
• Experience with cloud platforms such as Google Cloud Platform (GCP), including services like BigQuery, Cloud Storage, and AI Platform.
• GCP Professional Machine Learning Engineer certification is required.
• Experience with version control systems such as Git.
• Excellent problem-solving skills and attention to detail.
• Strong communication and collaboration skills.

Preferred Qualifications

• Master's degree or higher in Computer Science, Engineering, Mathematics, or a related field.
• Experience with distributed computing frameworks such as Apache Spark.
• Familiarity with containerization and orchestration technologies such as Docker and Kubernetes.
• Experience with data visualization tools such as Matplotlib, Seaborn, or Tableau.
• Experience with natural language processing (NLP) or computer vision (CV) techniques.
• Experience with continuous integration and continuous deployment (CI/CD) pipelines.
• Contributions to open-source projects or participation in relevant communities.