Machine Learning Engineer

Machine Learning Engineer (Azure Focus) - Remote (PST)

[About the Role]

Join GAP as a Machine Learning Engineer and lead the development, deployment, and optimization of innovative AI solutions in a fully remote environment. This six-month contract opportunity is tailored for engineers with a passion for hands-on machine learning in Microsoft Azure production settings. Collaborate with talented teams to create real business impact by delivering robust, scalable models for enterprise applications.

[Responsibilities]

- Design, build, and deploy machine learning models using neural networks and NLP techniques to solve business challenges

- Manage the complete ML lifecycle: data preparation, model selection, training, evaluation, deployment, and ongoing performance monitoring

- Leverage Python and ML frameworks (TensorFlow, PyTorch, Keras) to develop, optimize, and maintain models

- Implement MLOps best practices, including CI/CD pipelines, model versioning, and automated retraining in Azure environments

- Collaborate cross-functionally with data scientists, engineers, and stakeholders to deliver production-ready AI solutions

- Utilize Azure Machine Learning, Azure DevOps, and Azure Databricks for end-to-end ML operations

[Required Skills and Experience]

- Proven track record developing and deploying machine learning models into Microsoft Azure cloud platforms

- Hands-on expertise with neural networks and NLP methods (text classification, sentiment analysis, entity extraction, chatbots, or language models)

- Advanced proficiency in Python; practical experience with R and SQL for data extraction and statistical modeling

- Deep understanding of supervised and unsupervised learning algorithms, model evaluation, and optimization

- Mastery of modern ML frameworks (TensorFlow, PyTorch, Keras) in production

- Demonstrable experience in MLOps: CI/CD for ML, model monitoring, version control, retraining, and production support

[Preferred Skills]

- Experience with Azure Databricks, Azure Functions, and Azure Pipelines

- Familiarity with containerization (Docker/Kubernetes) for scalable ML deployments

- Strong feature engineering and ML pipeline automation skills

[Benefits]

- 100% remote work-collaborate with a diverse team from anywhere within PST hours

- Opportunity for contract extension and career progression on impactful enterprise AI projects

- Exposure to best-in-class Azure ML infrastructure and enterprise DevOps practices

[How to Apply]

Excited to build and deploy cutting-edge AI solutions in Azure? Submit your resume now. Qualified candidates will be contacted for an initial screening and technical interview.