Machine Learning Engineer
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Work Authorization: Candidates must be authorized to work in the United States
About the Role
We are looking for a talented and motivated Machine Learning Engineer to join our team in a fully remote position. The ideal candidate will have strong experience building, deploying, and maintaining machine learning models and data-driven solutions in production environments.
You will work closely with software engineers, data scientists, data engineers, and business stakeholders to develop scalable ML solutions that address real-world business problems.
Key Responsibilities
- Design, develop, train, and deploy machine learning models.
- Prepare, clean, and transform large datasets for machine learning applications.
- Develop scalable and reliable ML pipelines.
- Evaluate model performance and improve accuracy, efficiency, and scalability.
- Implement machine learning solutions in production environments.
- Collaborate with Data Scientists and Data Engineers on model development and deployment.
- Develop APIs and services to integrate ML models into applications.
- Monitor model performance and address model/data drift.
- Implement best practices for model versioning, testing, deployment, and monitoring.
- Work with cloud platforms to deploy and scale machine learning workloads.
- Document models, pipelines, experiments, and technical processes.
- Stay current with developments in machine learning, artificial intelligence, and MLOps.
Required Qualifications
- Bachelor's or Master's degree in Computer Science, Data Science, Artificial Intelligence, Statistics, Mathematics, or a related field.
- 1+ years of experience in Machine Learning Engineering, Data Science, or a related role.
- Strong programming skills in Python.
- Experience with machine learning frameworks such as Scikit-learn, TensorFlow, or PyTorch.
- Strong understanding of machine learning algorithms and statistical concepts.
- Experience working with SQL and structured/unstructured data.
- Experience building and deploying ML models in production.
- Strong understanding of software engineering principles, including Git, testing, and CI/CD.
- Strong analytical and problem-solving skills.
Preferred Qualifications
- Experience with AWS, Microsoft Azure, or Google Cloud Platform.
- Experience with Docker and Kubernetes.
- Knowledge of MLOps practices and tools.
- Experience with ML platforms such as MLflow, Kubeflow, SageMaker, Vertex AI, or Azure Machine Learning.
- Experience with NLP, recommendation systems, computer vision, or generative AI/LLMs.
- Experience working with distributed data processing frameworks such as Spark.
- Familiarity with REST APIs and microservices architecture.
- Experience working in Agile/Scrum environments.
What We Offer
- Fully remote work environment.
- Competitive compensation.
- Opportunity to work on challenging AI/ML projects.
- Professional development and learning opportunities.
- Collaborative and flexible work culture.
[Company Name] is an equal opportunity employer. We are committed to providing an inclusive workplace and consider qualified candidates without regard to legally protected characteristics under applicable federal, state, or local law.
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