Principal Machine Learning (ML) Engineer
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A Principal Machine Learning (ML) Engineer is a machine learning engineer that is a Principal Software Engineer.
- Example(s):
- They can (often) have a STEM PhD, such as PhD in Computing Science.
- They can lead ML Code Reviews.
- …
- Example(s):
- Counter-Example(s):
- See: Director of ML Engineering.
References
2020
- https://www.miletwo.us/join/principal-ml-engineer14.html
- QUOTE: The ML engineer will be a self-starter and technical leader that will help shape new directions in the organization and provide mentorship to others. Working closely with internal staff to take technologies to new intelligent software and services.
We are looking for ML engineers from all areas of machine learning and artificial intelligence who are passionate, can demonstrate ability for independent research and technical leadership, and have management experience. You will also have the opportunity to work closely with internal partners to see your ideas realized in products and services.
A principal machine learning engineer has a PhD in machine learning, statistics, computer science, physics, neuroscience or related field with two (2) or more years of related experience and will report directly to the director of engineering.
- Day-to-Day Responsibilities
- Plan, schedule, mentor, and lead the execution of projects and activities of the team
- You will be a trusted advisor for machine learning development who drives best practices and quality coding standards
- Translate technical requirements into specific tasks, correctly represent the urgency of issues, call out inconsistencies, and ultimately drive issues to closure
- Provide technical mentorship and guidance and prepare technical reports for publication and conference talks
- Additional job responsibilities as assigned
- What You Need to Bring
- Understanding of data structures, data modeling, and software architecture.
- Deep knowledge of math, probability, statistics, and algorithms.
- Expertise in at least one area of computer vision, machine learning, and computer graphics (e.g., deep convolutional neural networks, object detection, tracking, segmentation, AR/VR, image and video processing, 3D geometry, SLAM, multi-view geometry, simulation, graphics rendering.) Alternatively, expertise with state-of-the-art reinforcement learning and/or natural language processing (NLP) domains will be considered as well
- Experience with one or more deep learning framework such as PyTorch or Tensorflow.
- Desire to be involved in multiple diverse and innovative projects
- QUOTE: The ML engineer will be a self-starter and technical leader that will help shape new directions in the organization and provide mentorship to others. Working closely with internal staff to take technologies to new intelligent software and services.
2020
- https://hired.com/job/principal-machine-learning-engineer-anaplan
- QUOTE: ... What you'll be doing:
- Lead the coding and design of an evolving AI/Machine Learning and data pipeline including key infrastructure decisions.
- Build scalable machine learning processes that operate over billions of records, to develop predictive models and knowledge graphs that extract data from, among others, Supply Chain, Sales, Marketing, Finance, to IT to help our enterprise customers make better business decisions.
- Write efficient and well-organized software as part of the engineering team to deliver software in an iterative, continual-release environment.
- Monitor and plan out core infrastructure enhancements
- Drive understanding and buy-in among all stakeholders at all levels.
- Contribute to and promote good software engineering practices across the team.
- Mentor development teams globally (i.e. demonstrate good coding practices and helping them architect code)
- Lead code reviews, design sessions, and technical documentation.
- More about you:
- Coding fluency with a wide variety of data analysis and machine learning techniques
- Depth of experience building end-to-end enterprise solutions that leverage data analysis and machine learning
- Excellent communication skills for leading and explaining data science projects and system architecture choices
- Expertise with common Data Science tools and frameworks like: Python, scikit-learn, NLTK, Numpy, Pandas, TensorFlow, Keras, R, Spark
- Awareness of other data-intensive topics like: Operations Research, Optimization, NLP, Computer Vision, Decision analysis, Monte Carlo analysis, Simulation, etc.
- Experience working on either GCP, AWS or Azure for delivering Machine Learning solutions
- At least 5+ years in Data Mining, Data Pipelines, ETL, Training ML Models and Building Predictive Machines
- Experience working in a Linux or Unix environment
- Spark - working with RDDs and Data Frames to query and perform data manipulation or similar distributed data processing
- Source Control Management Tool - Git
- Stream processing technologies and concurrency frameworks
- Strong understanding of the nature of distributed development and its pitfalls
- BS in Computer Science, Engineering, Technology or related fields. Masters or PhD degree is a plus.
- QUOTE: ... What you'll be doing: