Machine Learning Engineer Job Description
Machine Learning Engineer Duties & Responsibilities
To write an effective machine learning engineer job description, begin by listing detailed duties, responsibilities and expectations. We have included machine learning engineer job description templates that you can modify and use.
Sample responsibilities for this position include:
Machine Learning Engineer Qualifications
Qualifications for a job description may include education, certification, and experience.
Licensing or Certifications for Machine Learning Engineer
List any licenses or certifications required by the position: AWS, GPEN, CEH, CISSP, SAS, SQS, SNS, S3, ISTQB, AI
Education for Machine Learning Engineer
Typically a job would require a certain level of education.
Employers hiring for the machine learning engineer job most commonly would prefer for their future employee to have a relevant degree such as Bachelor's and Master's Degree in Computer Science, Mathematics, Engineering, Machine Learning, Statistics, Technical, Science, Electrical Engineering, Physics, Graduate
Skills for Machine Learning Engineer
Desired skills for machine learning engineer include:
Desired experience for machine learning engineer includes:
Machine Learning Engineer Examples
Machine Learning Engineer Job Description
- Build complex data sets from multiple sources, both internally and externally
- Develop software modules based on algorithms and test them against real data
- Validate models and algorithms in the field
- Take the ownership of a significant part of the team’s solution development
- Work in a modern agile devops environment to deliver well-planned, tested, documented and maintainable code, using JIRA, Git and CI/CD technologies
- Design solution architecture in collaboration with team leads, with a focus on AWS/Azure cloud solutions but also including integration/deployment into other environments
- Share learnings with your team-mates in AAG ML/data engineering about theoretical and technical developments in our rapidly evolving field, collaborate with the open source community, and work together to create a great working environment that attracts other great engineering colleagues
- Act as an ambassador and coach towards engineering teams at our clients and partners to raise their capabilities and ensure that solutions are successfully deployed and maintained
- Build platform to enable lifecycle of billions of images, documents and other assets in Adobe Cloud
- Contributes to effort to revise current practices
- 1-3 years of experience developing deep learning models using tools such as Caffe, Tensorflow, Theano, Torch, Keras
- Must possess a strong background in Machine Learning
- Experience with GPU computing (CUDA) and deep learning libraries (TensorFlow, Caffe, Theano, ) is a plus
- BS and MS in Computer Science or related field with research in machine learning
- Thrive in an Agile, highly collaborative and team-oriented environment
- Enjoy solving challenging problems on a global scale
Machine Learning Engineer Job Description
- Ad hoc analysts and reporting as needed
- Bringing these techniques and the latest ML/DL frameworks and tools to NERSC users and the some of the world’s largest supercomputers
- Provide expert ML/DL advice and consultancy services to scientists and users of NERSC computing resources
- Evaluate and implement different algorithm to pick most applicable algorithm
- Scaling the model choice on large scale data in cloud
- Perform all activities in a safe and responsible manner and support all Environmental, Health, Safety & Security requirements
- Modeling complex problems and mining large data sets for insights
- Building predictive models in a production setting
- Hands on data cleanup and data preparation for deep analysis
- Analyzing and curating data sets
- PhD in Engineering degree (computer science, robotics, mathematics, statistics
- Solid foundation in Natural Language Processing or Machine Learning
- MS, or PhD in Computer Science/Statistics/Mathematics or related discipline
- 1 year+ experience with AWS, specifically S3, EC2, and EMR
- 1 year+ experience with Spark, HDFS, and related large data technologies
- Must be self-directed and self-motivated, able to work and learn independently * Strong math and algorithm background, especially for Machine Learning * 0-5 years experience * Must be comfortable in a Linux environment * Contributions to open source projects we can review is a plus * Fluent in C, C++, Python * Familiar with reading and coding assembly * Familiarity with NumPy, Halide, BLAS, Eigen, and/or TensorFlow a plus * Love of unit testing and automation
Machine Learning Engineer Job Description
- Working with a text, video, and images to extract useful metadata
- Collaborating across the team to shape the Data Platform technology stack
- Improving automation and test coverage (unit/integration/user acceptance tests, ) • Keeping up to date with modern data engineering technologies
- Improving automation and test coverage (unit/integration/user acceptance tests)
- Keeping up to date with modern data engineering technologies
- Lead software engineers and junior researchers
- Design, develop, and validated proposed ML solutions
- Deploy these solutions on a large scale where performance and maintainability are critical
- Improve the accuracy of existing algorithms to an acceptable level
- Improve the run-time of existing algorithms
- At least 1 year experience with leading big and fast data technologies like Spark, Scala, Akka, Cassandra, Accumulo, Hbase, Hadoop, HDFS, AVRO, MongoDB, or Mesos
- Proven expertise with autonomous vehicles or robotics
- Knowledge in rapid prototyping frameworks, ADTF, DDS, RTOS
- Some knowledge of machine learning strategies (neural nets, Bayesian algorithms, decision trees, ) and basic statistics (regression, sampling, normalization)
- Ability to analyze business requirements to assess feasibility of solutions
- Proven ability to be successful in cross-functional teams
Machine Learning Engineer Job Description
- Creates workflows that manage the development, support, and release of production level code
- Operationalizes applications into stable builds which can then be deployed to the cloud or on-prem
- Creates measurement systems to continuously evaluate the performance of data products
- Decomposes complex problem statements into specific deliverables and requirements
- Leads program review sessions and collaborative exercises to build the team's overall analytical capability
- Mentors junior team members and provides constructive critique on specific projects
- Develop tooling and infrastructure to support data scientists with model development
- Perform data analysis to generate customer specific business insights from Cloud application ac
- Architect, test, tune and deploy algorithms into production
- Partner with engineers and product managers to take ideas from inception to delivery
- 3+ years of experience in SQL databases with excellent SQL/T-SQL query writing and optimizing skills to create and maintain large summary & statistical data-sets with MySQL, Postgres, MS SQL Server or AWS Redshift
- 3+ year of experience in Amazon Web Services (AWS) technologies - Machine Learning, Redshift, S3, EC2, RDS, IAM, EMR with Spark and other data processing and analytics technologies
- Excellent business and communication skills to be able to develop and define key business questions to apply ML and the ability to work well in a team
- Experience working in a highly agile environment with aggressive sprint models
- Theoretical and practical understanding of machine learning algorithms in high-dimensional spaces including linear models, kernels, ensembles, dimensionality reduction, data mining, and clustering
- Fundamentals of algorithms and computational complexity, especially in scalable data-mining algorithms
Machine Learning Engineer Job Description
- Execute on research results to deploy production solutions
- Work with architecture and development to lay out technology vision for current and future product offerings
- Take ownership of a significant part of the team’s solution development
- Partner with ML researchers to push the boundaries on the performance of the latest methods applied to big problems within domains of insurance / investments
- Contribute to Peer Review process to ensure code quality
- Play an active role in the development and delivery of the team’s technology roadmap, and the design and delivery of necessary trainings and workshops
- Create and maintain platform documentation
- Turn smart, state-of-the arts analytics insights into results in real time
- Deliver proto-algorithms, specifications or actual code building upon NICE's proprietary NLP to solve a variety of problems and use cases
- Perform rigorous feature engineering and error analysis
- Demonstrated ability to solve real-world problems using machine learning given real-world data
- Ability to implement complex algorithms by hand
- Understanding of Machine Learning fundamentals
- At least one typed language
- At least one scripting language (e.g., Python)
- Understanding of authentication/ permissions/ security best practice