Machine Learning Engineer

We’re seeking a Machine Learning Engineer to support a leading industry company. This remote role is perfect for professionals with a passion for developing scalable AI solutions and working within cloud ecosystems. Join a dynamic team dedicated to driving innovation in healthcare and retail applications from anywhere outside the region. This opportunity is open for a contract duration exceeding one year, offering flexibility and the chance to impact critical systems.

There is no Final date to receive applications.

• Design, develop, and implement scalable machine learning models and data pipelines on cloud platforms.
• Build and maintain comprehensive end-to-end ML workflows, including feature engineering, model training, evaluation, deployment, and ongoing monitoring.
• Develop accessible ML capabilities through APIs for use by other systems and teams.
• Operationalize advanced models such as LLMs, SLMs, and retrieval-augmented systems to ensure high performance and scalability.
• Collaborate closely with data, software, and product teams to integrate ML solutions into broader infrastructure.

• Strong proficiency in Python programming with solid understanding of core machine learning principles.
• Hands‑on experience with Google Cloud Platform, especially Vertex AI for training and deploying models.
• Knowledge of containerized environments using Kubernetes and Docker for ML workloads.
• Experience working with NLP, including training and deploying language models, and hosting models in production.
• Familiarity with large‑scale data processing and management of the ML lifecycle.

• Medical, Dental, and Vision Insurance.
• Life Insurance.
• 401(k) Program.
• Commuter Benefit.
• eLearning and Ongoing Training.
• Education Reimbursement.

Eligibility requires working over 30 hours per week on an assignment lasting at least 10 weeks.

If you meet the qualifications and are excited about this opportunity, apply today! Our team will connect with you to discuss next steps, support you through the interview process, and advocate for your success.