Remote AI/ML Engineer — Production-Driven & MLOps

Talantir; United States; Remote; USD 125,000 - 130,000; Full time

Benefits offered by this job

Remote work

Job summary

Talantir is seeking an AI/ML Engineer with around 4 years of experience to design, develop, and deploy machine learning models and AI-driven applications. The role emphasizes scalable ML solutions, handling large datasets, and deploying models into production environments.

The ideal candidate collaborates with data scientists, engineers, and product teams, implements MLOps practices, and continuously improves model performance.

Qualifications

• Bachelor’s or Master’s degree in CS/AI/Data Science or related field.
• Minimum 4 years of experience in AI, ML, or data science roles.
• Strong programming skills in Python.
• Experience with ML frameworks such as TensorFlow, PyTorch, or Scikit-learn.
• Experience with Pandas, NumPy, and SQL.
• Knowledge of ML algorithms, NLP, or computer vision.
• Experience with cloud platforms such as AWS, Azure, or GCP.

Responsibilities

• Design, develop, and deploy machine learning and deep learning models.
• Build and maintain data pipelines and ML workflows for model training and inference.
• Collaborate with data scientists, engineers, and product teams to implement AI solutions.
• Perform data preprocessing, feature engineering, and model optimization.
• Deploy and monitor models in production environments.
• Implement MLOps practices for model lifecycle management.
• Evaluate model performance and continuously improve accuracy and efficiency.
• Document solutions and follow best practices in AI/ML development.

Education

Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, or related field

Tools

Python

TensorFlow

PyTorch

Scikit-learn

Pandas

NumPy

SQL

AWS

Azure

GCP

MLflow

Kubeflow

Docker

Kubernetes

Spark

Hadoop

Gen AI

LLMs

Transformers

NLP

Agile

Job description

Talantir is seeking an AI/ML Engineer with around 4 years of experience to design, develop, and deploy machine learning models and AI-driven applications. The role emphasizes scalable ML solutions, handling large datasets, and deploying models into production environments.

The ideal candidate collaborates with data scientists, engineers, and product teams, implements MLOps practices, and continuously improves model performance.