|Location||San Diego, CA|
|Date Posted||June 18, 2020|
Mitchell & Genex have Merged
Mitchell is a trusted software and service provider to the Property & Casualty Claims and collision repair industries as well as risk management professionals. We provide technology and services that simplify claims handling, repair processes and pharmacy transactions with best in class clinical management and cost containment solutions. Genex helps injured workers return to their jobs in a safe and efficient manner through compassionate case management, reducing health care costs and disability expenses for our customers.
Together, we bring two industry leaders in software and service committed to delivering a first-class experience to the customers, partners and markets we serve. We offer a complete suite of technology enabled solutions, and a proven managed care service mix, allowing us to deliver better outcomes to our clients for their businesses, their employees and their customers.
The APD Smart Solutions Team is looking for an extraordinary Machine Learning DevOps Engineer to join our team.
As a ML DevOps Engineers, you will craft, design and implement our machine learning strategy at scale to the innovative claims workflow lifecycle and help build the future of our claims automation journey.
You will be building, deploying and scaling ML/AI algorithms from Data centers and cloud hubs serving thousands of inferences daily in insurance claims workflow settings.
As a key member of our team, collaborate with different engineering and operations teams leading deployment of ML solutions for a variety of tasks and projects, delivering projects from end-to-end.
You will help the ML Engineers deliver applications with minimal delays at precisely the right resource footprint with elasticity, while ensuring absolutely tight and robust security, privacy and confidentiality. You are comfortable designing & enabling data pipelines to deploy AI/ML models at scale.
If you are passionate to influence the quality, speed and efficiency of our ML algorithms, come and help enable our vision to create the most refined products in the world.
- Deploy scalable Machine Learning and CNN based Computer Vision algorithms on local and multi cloud-based inferencing platforms.
- Designing and deploying models at scale using automated pipelines.
- Convert Python based ML scripts to production quality level applications.
- Test applications for stability, resilience, HA and scale them to serve thousands of inferences on a daily basis.
- Work closely with data Engineers, developers and Machine Learning engineering peers to integrate ML/AI models and applications with existing suite of APD smart products.
- Be approachable, a team player and ready to assist SRE & DevOps to build pipelines that need minimal operational maintenance.
- If needed, be ready to independently learn new technologies.
- Be able to prioritize tasks and take ownership.
- Ability to communicate and meaningfully present results of analyses in a clear and impactful manner.
Education & Experience
- BS in Computer Science/EE/CSE/DSE, or related fields with at least 4 years’ experience applying machine learning techniques to real business problems.
- Masters of Computer Science, Data Science and/or Machine Learning, or higher level degree preferred
- 3-4 years of knowledge of validated approaches for scale-ability, productionalizing AI/ML models and implementing machine learning applied to expansive and diverse datasets (storage GPUs/TPUs, techniques for deep learning at scale)
- Deployment of Machine Learning and Deep Learning algorithms on cloud based services (AWS Sage maker, GCP MLE, Digital Ocean, etc.)
- 3-4 years of expertise in configuration management systems CI/CD (Docker, Kubernetes, etc.)
- Version control (Git, Jenkins), Unix Shell scripting
- Experience or familiar with serverless architecture/ paradigm in cloud stack
- Experience with Image Analysis/Computer Vision is a plus
- Experience with Swift, Objective-C, Cocoa, Cocoa Touch, and/or CoreML
- Networking concepts and protocols, e.g.: TCP/IP, HTTP, etc.
- Knowledge or familiarity of ML algorithms (deep learning, classification, TensorFlow etc.)
- Preferred knowledge of Python libraries such as Scikit-learn, SciPy, Spacy, and NLTK
- Experience working in a Scaled Agile Framework (SAFe), and Test Driven Development.
Mitchell International, an equal opportunity employer, values the diversity of our workforce and the knowledge of our people. Mitchell will not discriminate against an applicant or employee on the basis of race, color, religion, national origin, ancestry, sex/gender, age, physical or mental disability, military or veteran status, genetic information, sexual orientation, gender identity, gender expression, marital status, or any other characteristic protected by applicable federal, state or local law.