AI Summary
We are seeking an AI/ML Engineer with 2-5 years of experience to build and enhance production machine learning systems. The role involves implementing core models, developing efficient data pipelines, and ensuring smooth operation of AI services. Candidates should have proficiency in Python and ML libraries, experience with SQL and cloud platforms, and strong communication skills.
Key Highlights
2-5 years of AI/ML engineering experience
Proficiency in Python and ML libraries (scikit-learn, PyTorch, TensorFlow)
Experience with SQL and cloud platforms (AWS, Azure, GCP)
Focus on production systems, MLOps, and model deployment
Key Responsibilities
Write, implement, and test machine learning algorithms and models under senior guidance
Develop and maintain efficient data pipelines and scripts for cleaning, transforming, and augmenting large datasets
Assist in iterative development, managing, and validating new features to improve model performance
Design and conduct rigorous A/B testing and validation experiments to measure model performance and impact
Work within existing MLOps frameworks (Docker, Kubernetes, MLflow) to deploy and manage models in cloud production environments
Quickly diagnose, debug, and resolve issues related to model performance, data pipelines, and production inference services
Help set up and maintain model monitoring tools to track key production metrics, latency, and data/model drift
Participate in agile ceremonies for sprint planning, communication, and delivery of sprint goals
Work closely with product owners and cross-functional team members to understand user stories and deliver solutions
Write clean, maintainable, and well-documented code and contribute to internal knowledge bases and documentation
Technical Skills Required
Benefits & Perks
Fully remote
Job Description
We are looking for an AI / Machine Learning Engineer with 2-5 years of experience to play a critical role in building and enhancing our production machine learning systems. You will be responsible for the day-to-day implementation of core models, developing efficient data pipelines, and ensuring the smooth operation of our AI services. This role is ideal for an engineer eager to solidify their production skills, learn MLOps best practices under senior guidance, and immediately contribute to impactful, user-facing features.
- This position is fully remote
- This role is an Individual Contributor position
- Write, implement, and test machine learning algorithms and models under the guidance of senior team members, focusing on defined project scopes.
- Develop and maintain efficient data pipelines and scripts for cleaning, transforming, and augmenting large datasets necessary for model training and evaluation.
- Assist in the iterative process of developing, managing, and validating new features to improve existing model performance.
- Design and conduct rigorous A/B testing and validation experiments to measure model performance and impact before and after deployment.
- Work within our existing MLOps frameworks (e.g., Docker, Kubernetes, MLflow) to help deploy and manage models in cloud production environments.
- Quickly diagnose, debug, and resolve issues related to model performance, data pipelines, and production inference services.
- Help set up and maintain model monitoring tools to track key production metrics, latency, and data/model drift.
- Participate in agile ceremonies to contribute to effective sprint planning, transparent communication, and the successful delivery of sprint goals.
- Work closely with product owners and other cross-functional team members to deeply understand user stories and deliver valuable solutions in alignment with sprint goals.
- Contribute to the continuous improvement of development processes and tools through active participation in team retrospectives and feedback loops.
- Write clean, maintainable, and well-documented code and contribute to the development and maintenance of internal knowledge bases and documentation repositories to facilitate information sharing and team learning.
- Stay current with relevant technologies and industry trends.
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- Proficiency in Python and fundamental familiarity with essential ML libraries (e.g., scikit-learn, PyTorch, TensorFlow).
- Solid understanding of core machine learning concepts, statistical methods, and common algorithm families (e.g., regression, classification, clustering).
- Experience with SQL and working with relational or NoSQL databases for data extraction and preparation.
- Good grasp of software development principles, version control, and unit testing practices.
- Basic experience or strong foundational knowledge of deploying applications or using services on a major cloud platform (AWS, Azure, or GCP).
- Proven ability to analyze data, interpret model results, and clearly communicate findings.
- Strong communication and collaboration skills, with the ability to effectively interact with cross-functional team members.
- Ability to work independently on assigned tasks and contribute actively as a valued member of a self-organizing team.
Browse our curated collection of remote jobs across all categories and industries, featuring positions from top companies worldwide.
- 2+ years of experience in machine learning engineering, data science or a related role.
- Bachelor's degree in Computer Science, Engineering, Mathematics, Statistics, or a related field (or equivalent practical experience).
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