Machine Learning Engineer

Jobaaj Com; United States; Remote; USD 90,000 - 135,000; Full time

Job summary

Jobaaj Com is hiring a Machine Learning Engineer to design, build, and deploy ML models at scale. You will work across the full ML lifecycle from experimentation to production, delivering impact through production systems.

The role emphasizes building ML pipelines, MLOps infrastructure, model monitoring, and collaboration with product, engineering, and data teams. Strong Python and ML frameworks experience is required; cloud and containerization skills are a plus.

Qualifications

• 0 to 2 years of experience in machine learning engineering or related role.
• Bachelor's or Master's degree in CS, Data Science, Engineering, or related field.
• Strong programming skills in Python.
• Hands-on experience with ML frameworks (TensorFlow, PyTorch, Scikit-learn).
• Experience deploying models using Docker, Kubernetes, and cloud platforms (AWS/GCP/Azure).

Responsibilities

• Design, build, and optimize ML models for production use cases.
• Develop and maintain ML pipelines for preprocessing, training, and deployment.
• Collaborate with data scientists to transition models to production.
• Build and manage MLOps infrastructure (CI/CD, monitoring).
• Monitor models for drift and retraining needs.
• Collaborate with product and engineering teams to define ML-driven solutions.

Skills

Python

ML frameworks

ML algorithms

Education

Bachelor's or Master's in CS/Data Science/Engineering

Tools

TensorFlow

PyTorch

Scikit-learn

Docker

Kubernetes

AWS

GCP

Azure

Job description

We are hiring a Machine Learning Engineer on behalf of our client. This role involves designing, building, and deploying machine learning models into production systems at scale. It's a great opportunity for someone who enjoys turning research and data into real-world, impactful products, and who's comfortable working across the full ML lifecycle from experimentation to deployment.

Role & responsibilities

• Design, build, and optimize machine learning models for production use cases
• Develop and maintain ML pipelines for data preprocessing, training, and deployment
• Collaborate with data scientists to transition models from research to production
• Build and manage MLOps infrastructure (model versioning, CI/CD, monitoring)
• Optimize model performance for latency, scalability, and accuracy
• Work with large-scale datasets and distributed computing frameworks
• Deploy models as APIs/microservices and integrate with existing systems
• Monitor deployed models for drift, performance degradation, and retraining needs
• Collaborate with product, engineering, and data teams to define ML-driven solutions
• Stay current with the latest ML/AI research, tools, and best practices

Preferred candidate profile

• 0 to 2 years of experience in machine learning engineering or related role
• Bachelor's/Master's degree in Computer Science, Data Science, Engineering, or related field
• Strong programming skills in Python (experience with Java/Scala a plus)
• Hands-on experience with ML frameworks (TensorFlow, PyTorch, Scikit-learn)
• Solid understanding of ML algorithms (supervised/unsupervised learning, deep learning, NLP, computer vision as relevant)
• Experience deploying models using Docker, Kubernetes, and cloud platforms (AWS/GCP/Azure)