Date Posted: 5/28/2019Apply Now
Title: Senior Distributed Software Engineer
Location: Palo Alto, CA
We are seeking an experienced Senior Distributed Software Engineers to scale Machine Learning and Financial Modeling algorithms.
Data Scientists and Quants spend a considerable amount of time exploring data, iterating over machine learning (ML) and financial modeling simulation experiments. We are looking for distributed engineers who are keen to lend their skills solving these extremely tough problems on x86 commodity hardware based open source distribution frameworks. Distributed engineers who have solved these problems in HPC grids or GPU clusters for Financial and scientific domains in the past or more recently used open source frameworks for ML will be uniquely suited for the role.
In this role, you will have the opportunity to leverage open source frameworks to scale compute and memory intensive machine learning, financial modeling and simulations algorithms. We believe that utilizing crowd knowledge based open source distribution platforms is the truly long-term way to distribute compute and memory intensive tasks to keep pace with ever increasing data and accuracy needs.
What You'll Be Doing:
Utilizing your GPU and HPC based ML, financial modeling and simulations distribution expertise and applying to open source framework-based distributions.
Crafting and implementing open-source Apache Spark and MapReduce based distributions of ML, AI and financial modeling solutions.
Engaging open source communities, including Apache MLLIB and others, for technical discussion and contribution.
Working with our partners and customers on deploying advanced machine learning and financial modeling solutions in public cloud or on-premise clusters.
Presenting technical solutions in industry conferences and meetups.
What We Need to See:
You have a BS, MS, or PhD in Computer Science, Computer Engineering, Applied Math or closely related field
8+ years of work or research experience in software development
4+ years of hands on experience with key open source big-data ML projects or alternately with MPI, CUDA based HPC platforms
Extensive experience distributing ML and financial modeling and simulations
Exceptional technical skills in designing and implementing high-quality distributed systems
Excellent programming skills in C++, Java, Scala and/or Python
Knowledge about distributed system scheduler: Kubernetes, Hadoop YARN, Spark standalone, and/or Mesos
Able to work successfully with multi-functional teams across organizational boundaries and geographies
Highly motivated with strong communication skills
Ways to Stand Out From the CrowdCommitter-ship at major open source big-data projects (such as Apache Spark, MLLIB, Apache Mahout, Apache MapReduce) or open-source significant ML or financial modeling technique in Spark or MapReduce would be a hug plus
Deep experience with GPU or HPC based libraries (CUDA, MPI, cuBLAS, cuSparse, NCCL, nvGraph) is a good alternative
With competitive salaries and a comprehensive benefits package, we are widely considered to be one of the technology startup world's most desirable employers. We have some of the most forward-thinking and talented people in the world working for us. Are you creative and autonomous? Do you love a challenge? If so, we want to hear from you.
We are an equal opportunity employer and make hiring decisions based on merit. Recruitment, hiring, training, and job assignments are made without regard to race, color, national origin, age, ancestry, religion, sex, sexual orientation, gender identity, gender expression, marital status, disability, or any other protected classification. We consider all qualified applicants, including those with criminal histories, in a manner consistent with state and local laws, including the City of Los Angeles' Fair Chance Initiative for Hiring Ordinance.
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