Avitas Systems is a BHGE venture advancing the broad O&G industry through predictive data analytics, robotics, computer vision and artificial intelligence. Its solutions increase safety and efficiency of inspections and operations by providing state-of-the-art robotic-based autonomous inspection management and a cloud-based platform that stores, fuses, and analyzes comprehensive inspection and operational data.
The Machine Learning Engineer will be a key member of the Data Analytics and Machine Learning team who will be responsible for curating and analyzing a variety of business and operations data of Avitas Systems and BHGE customers across O&G and related industry verticals. Avitas Systems deals with huge volumes of real-world data originating from robotic and fixed sensors, Scada systems, inspections, and other sources. This is an opportunity to make an impact across the O&G industry in a fast-paced environment where rapid prototyping and experimentation are prized.
This specific role is responsible for designing and implementing production-grade end-to-end data and algorithm solutions, including fusing disparate data that originates from customers, applying cutting edge analytics models, and returning results that deliver value to customers. The Machine Learning Engineer will work closely with data scientists, product managers and backend engineers to gather requirements, understand performance characteristics, and identify usage patterns to deliver solutions that bring our model-driven products to market faster while also being robust and scalable.
In the role of the Machine Learning Engineer, you will:
* Establish processes for data and modeling lifecycle, i.e. managing the transitions from PoC to production
* Advocate for best practice software engineering principles
* Constantly strive to optimize (through automation/performance improvement/etc.) all aspects of data and model infrastructure
* Learn and stay up to date with industry best practices for production-grade machine learning systems
* Collaborate with cross-functional teams across multiple offices and regions
* Bachelor's Degree in Computer Science or related technical field from an accredited college or university
* Minimum 3 years of industry work experience
* M.S. or Ph.D. in Computer Science or related technical field
* Experience and interest in machine learning and AI, and in working with real world data sets
* Production-quality developer in Python, C/C , Java, or other general-purpose language
* Fluent with software development best practices, including version control, documentation, testing and CI/CD
* Experience with cloud infrastructure (AWS/Azure), particularly cloud storage (S3, Redshift) and computing (EC2, EMR)
* Experience with production database systems (e.g. Postgres) and technologies
* Experience with big data frameworks such as Cassandra, Spark and Hadoop
* Familiar with data processing tools such as Apache Beam, AWS Data Pipeline and GCP Dataflow
* Familiar with ML lifecycle tools such as MLflow, FBLearner Flow, TFX and Michelangelo
* Demonstrated awareness of how to succeed in ambiguous circumstances
* Experience with commercialization of analytics-driven applications / SaaS
* Experience with analytics development for industrial applications in a commercial setting
* Experience with virtualization and containerization, including managing and deploying containers using Kubernetes/Docker
* Experience with frameworks for distributed orchestration of multiple workloads such as Airflow and Celery
* Familiar with analytics frameworks and languages such as TensorFlow, Sci-kit learn, Spark, Scala, R, Python, MATLAB, etc.
* System Engineering and API based integration experience for large production systems
* Field experience working with customers and clients
* Experience in working with physics-based (or mechanistic) models
* Boston, MA 02108 or San Ramon, CA
This is your opportunity to learn more, do more, live the career you have imagined and be part of a truly diverse organization.
Baker Hughes, a GE company is an Equal Opportunity Employer. Employment decisions are made without regard to race, color, religion, national or ethnic origin, sex, sexual orientation, gender identity or expression, age, disability, protected veteran status or other characteristics protected by law. Learn more