Democratizing Recruitment
Job Description

AI/ML (Artificial Intelligence/Machine Learning) Engineer

Intelligence and Data
Department Mission
  • To advance the organization by developing algorithms to build artificial inteligence and machine learning models that uncover connections and make better decisions without human intervention.
  • Experimentation is at the core of what you do. The role is to work to turn business questions into data analysis effectively and provide meaningful recommendations. This is a unique hybrid role that will focus on your knowledge of data infrastructure and your ability to drive insights.
  • Develop models and train them,
  • Research on new technologies,
  • Participate in recruitment process.
  • Develop highly scalable systems, algorithms, and tools on one platform to support machine learning and deep learning solutions,
  • Develop, integrate, and optimize end to end AI pipeline,
  • Collect, analyze, and synthesize requirements and bottleneck in the technology, systems, and tools used by machine learning engineers and scientists, develop solutions that improve efficiency, leverage more amount of data efficiently,
  • Adapt standard machine learning methods to best exploit modern parallel environments (e.g. distributed clusters, multicore SMP, GPU, TPU and FPGA),
  • Explore state-of-the-art deep learning techniques,
  • Partner with data science and domain engineering teams to support the business transformation through AI.
  • University or advanced degree in engineering, computer science, mathematics, or a related field,
  • 5+ years experience developing and deploying machine learning systems into production,
  • Strong experience working with a variety of relational SQL and NoSQL databases,
  • Strong experience working with big data tools: Hadoop, Spark, Kafka, or etc,
  • Experience with at least one cloud provider solution (AWS, GCP, Azure),
  • Strong experience with object-oriented/object function scripting languages: Python, Java, C++, Scala, or etc,
  • Ability to work in a Linux environment,
  • Industry experience building innovative end-to-end Machine Learning systems,
  • Ability to quickly prototype ideas and solve complex problems by adapting creative approaches,
  • Experience working with distributed systems, service-oriented architectures and designing APIs,
  • Strong knowledge of data pipeline and workflow management tools,
  • Expertise in standard software engineering methodology, e.g. unit testing, test automation, continuous integration, code reviews, design documentation,
  • Relevant working experience with Docker and Kubernetes is a big plus.

It's always a good idea to include the benefits of the job the company will provide such as:

  • Flexible hours to give you freedom and increase productivity
  • Life insurance for you and your family members
  • Work remotely in the comfort of your home
  • Free Gym membership so you can stay in shape
  • Fun and energetic weekly team bonding events
  • etc.

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