Fluke Networks, Inc.
Data Science Engineer
Fluke Networks, Inc., Seattle, Washington, us, 98127
Join Fluke - India and be part of our innovative journey in electronics manufacturing. We are integrating cutting-edge AI and ML technologies to enhance our capabilities and drive growth. As a global leader, Fluke adopts a data-driven approach, ensuring precision and efficiency in every aspect of our operations. This offshore role offers a unique opportunity to work on advanced AI services and automation tools.
At Fluke, we’re revolutionizing customer experiences with state-of-the-art AI and machine learning models. Our team of experts is dedicated to unlocking new frontiers in AI, shaping the next generation of intelligent technologies. For over 25 years, we’ve been pioneering AI solutions to solve global challenges and open new possibilities.
We seek the brightest minds from diverse backgrounds to create transformative AI and ML solutions. Join us in improving lives, advancing universal agents, and shaping the future of robotics.
Key job responsibilities include:
Collaborate with experienced cross-disciplinary teams to conceive, design, and market innovative AI products and services. Enhance and optimize vector databases and knowledge graphs, including proficiency in configuring vectors and writing and optimizing Cypher queries. Develop and implement cutting-edge AI technologies in a large, distributed computing environment, driving fundamental industry changes. Create solutions for running predictive models on distributed systems, leveraging innovative technologies at scale and speed. Design and build scalable, fault-tolerant distributed storage, index, and query systems that are cost-effective and easy to manage and use. Translate broadly defined problems into concrete, effective solutions through robust design and coding practices. Work in an agile environment to deliver high-quality AI software efficiently. Focus on developing AI tools utilizing Large Language Models (LLMs) to address business challenges and boost productivity. Apply optimization mathematics, including linear programming and nonlinear optimization, to enhance AI solutions. The preferred candidate will have:
A Master's in Computer Science, Computer Engineering, Data Science, Electrical Engineering, or related fields. At least 7 years of professional experience in developing AI tools and solutions, with a strong focus on utilizing AI LLM models to solve business problems and enhance productivity. Proven experience in mentoring and developing junior developers, fostering their growth and ensuring high standards of coding and problem-solving skills. Extensive experience with distributed systems, algorithms, and relational databases. Strong understanding of computer science fundamentals including object-oriented design, operating systems, algorithms, data structures, and complexity analysis. Proficiency in one or more modern programming languages such as Java, Python, C++, or C#, including object-oriented design. Experience with Databricks on Azure and MS Fabric. Experience with distributed, multi-tiered systems, algorithms, and relational databases. Experience in optimization mathematics such as linear programming and nonlinear optimization. Ability to design and build scalable, fault-tolerant distributed storage, index, and query systems that are easy to manage and use. Experience working in an agile environment to deliver high-quality software efficiently. Strong interests and academic qualifications/research focus in Artificial Intelligence, machine learning, and/or Generative AI, such as computer vision, deep learning models, XLA, TVM, MLIR, and LLVM.
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Collaborate with experienced cross-disciplinary teams to conceive, design, and market innovative AI products and services. Enhance and optimize vector databases and knowledge graphs, including proficiency in configuring vectors and writing and optimizing Cypher queries. Develop and implement cutting-edge AI technologies in a large, distributed computing environment, driving fundamental industry changes. Create solutions for running predictive models on distributed systems, leveraging innovative technologies at scale and speed. Design and build scalable, fault-tolerant distributed storage, index, and query systems that are cost-effective and easy to manage and use. Translate broadly defined problems into concrete, effective solutions through robust design and coding practices. Work in an agile environment to deliver high-quality AI software efficiently. Focus on developing AI tools utilizing Large Language Models (LLMs) to address business challenges and boost productivity. Apply optimization mathematics, including linear programming and nonlinear optimization, to enhance AI solutions. The preferred candidate will have:
A Master's in Computer Science, Computer Engineering, Data Science, Electrical Engineering, or related fields. At least 7 years of professional experience in developing AI tools and solutions, with a strong focus on utilizing AI LLM models to solve business problems and enhance productivity. Proven experience in mentoring and developing junior developers, fostering their growth and ensuring high standards of coding and problem-solving skills. Extensive experience with distributed systems, algorithms, and relational databases. Strong understanding of computer science fundamentals including object-oriented design, operating systems, algorithms, data structures, and complexity analysis. Proficiency in one or more modern programming languages such as Java, Python, C++, or C#, including object-oriented design. Experience with Databricks on Azure and MS Fabric. Experience with distributed, multi-tiered systems, algorithms, and relational databases. Experience in optimization mathematics such as linear programming and nonlinear optimization. Ability to design and build scalable, fault-tolerant distributed storage, index, and query systems that are easy to manage and use. Experience working in an agile environment to deliver high-quality software efficiently. Strong interests and academic qualifications/research focus in Artificial Intelligence, machine learning, and/or Generative AI, such as computer vision, deep learning models, XLA, TVM, MLIR, and LLVM.
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