Application Development - Machine Learning Engineer I

Compunnel, Inc.; San Francisco (CA); On-site; USD 90,000 - 130,000; Part time

Job summary

Compunnel, Inc. seeks a Machine Learning Engineer I to develop, implement, and deploy ML solutions that support innovative products and applications in a production-ready environment.

You will build data pipelines, train and validate models, and collaborate with cross-functional teams to deliver scalable AI solutions. The role emphasizes hands-on implementation and documentation across the ML lifecycle.

Qualifications

• Bachelor's degree or equivalent in a technical field.
• 1–3 years of professional ML experience.
• Experience with ML, deep learning, data mining, and statistics techniques.
• Experience training, deploying, and monitoring ML models.
• Strong programming skills in Python, Java, or Scala.
• Experience developing and maintaining data pipelines.
• Knowledge of cloud and distributed data technologies such as Kafka, Spark, and Docker.
• Strong analytical, problem-solving, and communication skills.
• Ability to work collaboratively in a team-oriented development environment.

Responsibilities

• Implement, refine, and validate ML algorithms for products and applications.
• Develop and maintain data pipelines for data ingestion, validation, cleaning, and monitoring.
• Train, validate, and deploy ML models into production environments.
• Evaluate model performance and ensure accuracy and reliability of deployed solutions.
• Assist in developing POC solutions to support future product and application development.
• Research, prepare, and maintain technical documentation including requirements, evaluation plans, papers, presentations, tests, and reports.
• Test, evaluate, and validate ML solutions through case studies and performance analysis.
• Collaborate with engineering and cross-functional teams to support solution development and deployment.

Skills

Python

Java

Scala

Machine learning

Deep learning

Data mining

Statistical analysis

Data pipelines

Kafka

Spark

Docker

Cloud technologies

Analytical thinking

Communication

Education

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

Tools

Kafka

Spark

Docker

Job description

07/29/2026

Contract

Active

Job Description:

Job Summary

We are seeking a Machine Learning Engineer I to develop, implement, and deploy machine learning solutions that support innovative products and applications. The ideal candidate will have experience building data pipelines, training and validating machine learning models, and collaborating with cross-functional teams to deliver scalable, production-ready AI solutions.

Key Responsibilities

• Implement, refine, and validate machine learning algorithms for products and applications.
• Develop and maintain data pipelines for data ingestion, validation, cleaning, and monitoring.
• Train, validate, and deploy machine learning models into production environments.
• Evaluate model performance and ensure the accuracy and reliability of deployed solutions.
• Assist in developing proof-of-concept (POC) solutions to support future product and application development.
• Research, prepare, and maintain technical documentation, including technical requirements, evaluation plans, white papers, presentations, test results, and reports.
• Test, evaluate, and validate machine learning solutions through case studies and performance analysis.
• Collaborate with engineering and cross-functional teams to support solution development and deployment.

Required Qualifications

• Bachelor's degree in Computer Science, Computer Engineering, Mathematics, or a related technical field, or equivalent industry experience.
• 1–3 years of professional experience in machine learning or a related field.
• Experience with machine learning, deep learning, data mining, and statistical analysis techniques.
• Experience training, deploying, and monitoring machine learning models.
• Strong programming skills in Python, Java, or Scala.
• Experience developing and maintaining data pipelines.
• Knowledge of cloud and distributed data technologies such as Kafka, Spark, and Docker.
• Strong analytical, problem-solving, and communication skills.
• Ability to work collaboratively in a team-oriented development environment.