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Falkonry: Machine Learning Research Engineer [Sunnyvale, CA]


Falkonry is seeking a Machine Learning Research Engineer, ideal for someone who wants to apply their quantitative talents to real-world opportunities in the most efficient manner possible - designing the intelligent core of a system that subject matter experts can use to comprehend, diagnose, and monitor increasingly complex systems.



At: FalkonryFalkonry
Location: Sunnyvale, CA
Web: falkonry.com
Position: Machine Learning Research Engineer

Apply here.

About Falkonry

Predictive operations are creating a unique opportunity to deliver billions of dollars in value by improving throughput, quality and safety. This opportunity is global and is transforming every manufacturing and process industry, as illustrated in our Use Case Guide.

Falkonry is the leader in predictive operations, with a rapidly growing list of customers from Global 2000 companies. Our Falkonry LRS product enables operations teams to discover, explain and predict behaviors in their operations without requiring data scientists.

We are backed by well-known Silicon Valley and corporate venture firms. We are passionate about our customers’ success and have assembled a highly accomplished team of engineers, entrepreneurs and business leaders. We offer a fun, diverse, and flexible environment with competitive salary, equity, benefits and generous paid time off.

Position

Our machine-learning research engineer position is ideal for someone who wants to apply their quantitative talents to real-world opportunities in the most efficient manner possible - designing the intelligent core of a system that subject matter experts can use to comprehend, diagnose, and monitor increasingly complex systems.

You will work closely with the product and engineering teams, and occasionally with select customers, to establish new methods and capabilities. Some notable aspects of your work at Falkonry include semi-supervision, automated feature extraction, explainability, and few-shot learning.

Responsibilities

  • Identify, adapt, invent, and assess algorithms for timeseries data analysis
  • Identify and prioritize opportunities to productize new ML-driven capabilities
  • Help our engineers apply ML capabilities to large data volumes and with low latencies
  • Track and assess leading-edge academic and competitive techniques
  • Help raise the profile of predictive operations challenges in both academia and industry

Qualifications

  • PhD or equivalent experience in a relevant discipline
  • Broad familiarity with common machine-learning and signal processing techniques
  • Strong practical data manipulation skills
  • Excellent verbal and written communication skills

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