SKAEL, a global leader in hyperautomation, provides a no-code digital workforce platform that helps companies of all sizes automate across disparate applications, data sources and documents, while engaging users where they are – email, text, voice, and video communication channels. While hyperautomation is the combination of RPA, ML and NLP, it isn’t just about technologies. It’s about rapidly and systematically identifying, vetting and automating as many business processes as possible, with a focus on increasingly making AI-driven decisions.
SKAEL’s mission is to deliver better user-centric outcomes through intelligent cognitive automation, empowering a synergistic human digital workforce. The company has been headquartered in San Francisco since its founding in 2016.
About the Group
The SKAI (SKAEL AI) group is in charge of developing and enhancing advanced technologies, such as artificial intelligence, machine learning and data mining, to advance SKAEL’s business and products. The group works on programs in multiple areas such as conversational AI, data wrangling, image processing, behavioral analytics, predictive analytics, business enablement, telemetrics and benchmark analytics. By leveraging advanced technologies and sophisticated algorithms, SKAI’s solutions empower SKAEL’s intelligent digital employees. SKAI comprises data scientists, AI architects, ML engineers and data engineers, and reports to the company’s Chief AI Officer.
Key Responsibilities
As an MLOps Engineer at SKAEL, you will have a chance to be part of a team that works on cutting-edge technologies, particularly NLP, and a variety of AI/ML algorithms that improve the way human employees interact with digital employees.
As part of your role, you may need to:
Build data pipelines that collect, manipulate and process information
Create conceptual and logical models for the data infrastructure
Extract and manipulate large datasets using tools such as Python and SQL
Drive the collection of new data and the refinement of existing data from a variety of sources
Create data structures on the cloud, including queues, stacks and graph databases
Establish data engineering processes designed to efficiently and reliably deploy ML models to production
Evaluate data structure tools and technologies to determine fit
Communicate complex concepts and the results of the analyses in a clear and effective manner
Collaborate with other team members and cross-functionally to share knowledge and discuss initiatives
Minimum Qualifications
A degree in Computer Science, Computer Engineering, Data Science, AI or a related field from an accredited institution
2+ years of experience in Python
Well versed with machine learning fundamentals
Track record with databases and data management: NoSQL and SQL, data ingestion / ETL, and data modeling
3+ years of experience as a DevOps or MLOps Engineer. Able to pass a technical interview
Experience in containerization and orchestration (such as Docker, Kubernetes)
Expertise in CI/CD development in the machine learning space
Self starter, able to work independently under tight deadlines
Prepared to work in a team environment and effectively collaborate with other team members to deliver joint solutions
Can share results and communicate clearly with team members and stakeholders, even in non-technical forums
Additional Job Information
Remote: Work from home
SKAEL provides a comprehensive benefit package, a flexible work environment and generous paid time off. We have a flat, open structure, a team that is dedicated to our core values, and provide you with an opportunity to change the world of work.
We are an equal opportunity employer and value diversity and inclusion at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.
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