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and applications.
• Monitor and maintain deployed models, making updates as needed.
Collaboration:
• Work closely with cross-functional teams, including data scientists, software engineers, and domain experts, to understand business requirements and develop...
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Machine Learning Engineer
Unreal Gigs | San Francisco | Full-time | apply.workable.com |
Company Overview: Welcome to the forefront of machine learning innovation! At our company, we're dedicated to harnessing the power of artificial intelligence to drive real-world impact. Our mission is to develop cutting-edge machine learning solutions that empower businesses and revolutionize industries.
Join us and be part of a dynamic team committed to pushing the boundaries of what's possible in AI.
Position Overview: As a Machine Learning Engineer, you'll play a pivotal role in developing and deploying state-of-the-art machine learning models and systems. Working closely with data scientists, software engineers, and domain experts, you'll tackle complex challenges and deliver scalable, robust solutions.
If you're passionate about leveraging data to drive innovation and eager to make a meaningful impact, we want you on our team.
Requirements
Key Responsibilities:
1. Model Development: Design, implement, and optimize machine learning algorithms and models to solve real-world problems across diverse domains, including but not limited to natural language processing, computer vision, and predictive analytics.
2. Data Processing: Develop data pipelines to ingest, clean, and preprocess large-scale datasets, ensuring data quality and integrity for training and evaluation.
3. Model Training and Evaluation: Train machine learning models using appropriate algorithms and techniques, evaluating model performance and iteratively refining approaches to achieve desired outcomes.
4. Model Deployment: Architect scalable and reliable machine learning pipelines for deployment in production environments, collaborating with DevOps engineers to ensure seamless integration and monitoring.
5. Performance Optimization: Optimize machine learning models and systems for speed, efficiency, and scalability, utilizing techniques such as distributed computing and parallel processing.
6. Cross-Functional Collaboration: Collaborate with cross-functional teams, including data scientists, software engineers, and product managers, to define requirements, prioritize tasks, and deliver solutions that meet business objectives.
7. Documentation and Reporting: Prepare documentation and technical reports to communicate model designs, implementation details, and performance metrics to stakeholders, ensuring transparency and reproducibility.
Qualifications:
• Bachelor's degree or higher in Computer Science, Electrical Engineering, Statistics, or related field.
• Strong background in machine learning, with hands-on experience in developing and deploying machine learning models in production environments.
• Proficiency in programming languages such as Python, TensorFlow, PyTorch, or scikit-learn, with experience in data manipulation and analysis.
• Familiarity with machine learning concepts and techniques, including supervised and unsupervised learning, deep learning, and reinforcement learning.
• Experience with cloud platforms such as AWS, Azure, or Google Cloud, and proficiency in using relevant tools and services for data storage, processing, and deployment.
• Strong problem-solving abilities and analytical thinking, with a keen attention to detail and a passion for tackling complex technical challenges.
• Excellent communication and collaboration skills, with the ability to work effectively in cross-functional teams and communicate technical concepts to non-technical stakeholders.
Benefits
• Competitive salary: The industry standard salary for Machine Learning Engineers typically ranges from $150,000 to $230,000 per year, depending on experience and qualifications. Exceptional candidates may be eligible for higher compensation packages.
• Comprehensive health, dental, and vision insurance plans.
• Flexible work hours and remote work options.
• Generous vacation and paid time off.
• Professional development opportunities, including access to training programs, conferences, and workshops.
• State-of-the-art technology environment with access to cutting-edge tools and resources.
• Vibrant and inclusive company culture with team-building activities and social events.
• Opportunities for career growth and advancement within the company.
• Exciting projects with real-world impact across diverse industries.
• Chance to work alongside top talent and industry experts in the field of machine learning.
Join Us: Ready to shape the future of AI with machine learning? Apply now to join our team and be part of an exciting journey of innovation and discovery!
Join us and be part of a dynamic team committed to pushing the boundaries of what's possible in AI.
Position Overview: As a Machine Learning Engineer, you'll play a pivotal role in developing and deploying state-of-the-art machine learning models and systems. Working closely with data scientists, software engineers, and domain experts, you'll tackle complex challenges and deliver scalable, robust solutions.
If you're passionate about leveraging data to drive innovation and eager to make a meaningful impact, we want you on our team.
Requirements
Key Responsibilities:
1. Model Development: Design, implement, and optimize machine learning algorithms and models to solve real-world problems across diverse domains, including but not limited to natural language processing, computer vision, and predictive analytics.
2. Data Processing: Develop data pipelines to ingest, clean, and preprocess large-scale datasets, ensuring data quality and integrity for training and evaluation.
3. Model Training and Evaluation: Train machine learning models using appropriate algorithms and techniques, evaluating model performance and iteratively refining approaches to achieve desired outcomes.
4. Model Deployment: Architect scalable and reliable machine learning pipelines for deployment in production environments, collaborating with DevOps engineers to ensure seamless integration and monitoring.
5. Performance Optimization: Optimize machine learning models and systems for speed, efficiency, and scalability, utilizing techniques such as distributed computing and parallel processing.
6. Cross-Functional Collaboration: Collaborate with cross-functional teams, including data scientists, software engineers, and product managers, to define requirements, prioritize tasks, and deliver solutions that meet business objectives.
7. Documentation and Reporting: Prepare documentation and technical reports to communicate model designs, implementation details, and performance metrics to stakeholders, ensuring transparency and reproducibility.
Qualifications:
• Bachelor's degree or higher in Computer Science, Electrical Engineering, Statistics, or related field.
• Strong background in machine learning, with hands-on experience in developing and deploying machine learning models in production environments.
• Proficiency in programming languages such as Python, TensorFlow, PyTorch, or scikit-learn, with experience in data manipulation and analysis.
• Familiarity with machine learning concepts and techniques, including supervised and unsupervised learning, deep learning, and reinforcement learning.
• Experience with cloud platforms such as AWS, Azure, or Google Cloud, and proficiency in using relevant tools and services for data storage, processing, and deployment.
• Strong problem-solving abilities and analytical thinking, with a keen attention to detail and a passion for tackling complex technical challenges.
• Excellent communication and collaboration skills, with the ability to work effectively in cross-functional teams and communicate technical concepts to non-technical stakeholders.
Benefits
• Competitive salary: The industry standard salary for Machine Learning Engineers typically ranges from $150,000 to $230,000 per year, depending on experience and qualifications. Exceptional candidates may be eligible for higher compensation packages.
• Comprehensive health, dental, and vision insurance plans.
• Flexible work hours and remote work options.
• Generous vacation and paid time off.
• Professional development opportunities, including access to training programs, conferences, and workshops.
• State-of-the-art technology environment with access to cutting-edge tools and resources.
• Vibrant and inclusive company culture with team-building activities and social events.
• Opportunities for career growth and advancement within the company.
• Exciting projects with real-world impact across diverse industries.
• Chance to work alongside top talent and industry experts in the field of machine learning.
Join Us: Ready to shape the future of AI with machine learning? Apply now to join our team and be part of an exciting journey of innovation and discovery!
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