Staff Machine Learning Algorithm Engineer

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Job updated over 3 years ago

Job Description

**Job Functions**

- Algorithm Engineer and Distributed System Architectures
- AI / Data Science / Machine Learning Algorithm Optimization
- Build the scalable ML platform to automate ML services.
- R&D Team Lead (3~10 members)

**Your Impact**

- Participate in cutting edge research in machine intelligence and machine learning platform.
- Build the next generation of AutoML and time series forecasting technologies, including automated data cleaning, pre-processing, feature engineering, feature selection, hyperparameter tuning, model training and scoring, stacking, ensembling and deep learning. (We're 110x faster than Google AutoML)
- Partner with product and research teams to identify opportunities for improvement in our current product line (Decanter AI) and for enabling upcoming product lines.
- Develop prototypes, then design and carry out experiments to validate and improve the prototypes.
- Develop solutions for real world, large scale problems.
- Bring the ideas to production.

Requirements

**MoBagel R&D Qualifications**

- Experience building new products that leverage challenging high-performance algorithms.
- Expertise in coding efficient, object-oriented, modularized and quality software.
- Exceptional debugging, testing, and problem-solving skills.
- Knowledge of unit testing, profiling, and code tuning.
- Passion for software development and problem solving.
- High energy, self-starter with aptitude for learning new technologies.
- Be able, and willing, to multi-task and learn, share, and improve technologies quickly.
- Experience with the Decanter AI or other AutoML software products.
- Ability to drive cross team collaborations and ship production features in a fast-paced startup environment.
- Superior communication skills, both verbal and written.
- Customer/end result driven in design and development

**Staff-level Key Qualifications**

- Master’s degree or PhD in Engineering, Computer Science, Statistics and Data Science, Mathematics or a related technical, quantitative field.
(Candidates with a bachelor’s and significant appropriate experience will also be considered.)
- 5 years(PhD)/ 8 years(Master) of relevant work experience in software development or data science related field.
- Expertise with Java/Scala, OOP, Design Patterns, time and space-efficient algorithms
- Experience architecting and developing distributed systems design.

**Preferred Qualifications**

- Experience architecting in Data Science and Machine Learning with a strong proven track record and significant impact.
- Knowledgeable in area pertaining to prediction such as statistics, machine learning for classification and regression, time series forecasting and reinforcement learning
- Proficiency in the mathematics underlying ML including linear algebra, multivariate statistics, information theory and optimization.
- Significant experience optimizing code to be both compute and memory efficient
- Demonstrated expertise working with one or more of the following: Big Data Infrastructure, Distribute System and Job Queue management, Machine Learning System, Time Series Forecasting, Algorithmic Foundations of Optimization, Data Mining or Machine Intelligence (Artificial Intelligence).
- Contributions to research communities/efforts, including publishing papers in machine learning (ICML, AAAI).
- Hands on technical leadership experience leading project teams and setting technical direction. Demonstrated experience providing technical leadership to development teams. (5~20 members)
- Experience motivating others to act by creating a shared sense of vision or purpose, ability to create a compelling vision for the future, communicate clearly, with a collaborative leadership approach.

若有興趣應徵此職位,麻煩填寫此表單,讓我們能夠更了解您:
https://mobagel.com/tw/jobs/#typeform

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MoBagel 行動貝果有限公司
Artificial Intelligence / Machine Learning
51 - 200 people

About us

Company Overview

MoBagel is a key vendor of a no-code AI/ML platform, as recognized by Gartner in 2020, 2021, and 2022. Decanter AI, the no-code AI/ML platform, empowers data scientists and domain experts to design and build AI solutions together. Through partnerships with key partners such as Dentsu Group, Deloitte and JETRO to build no-code AI solutions together, Decanter AI has quickly accumulated over 100,000 users and is well-positioned to continue driving innovation and growth for sustainability.

MoBagel is an AI startup based in Silicon Valley, founded by AI scientists from Stanford and UC Berkeley in 2015. MoBagel provides a generative AI platform and various enterprise-level AI Agents designed to enhance data-driven decision-making and business process automation. Recognized by Gartner for the past five years, MoBagel's platform empowers over 11,000 brands across industries such as sales and marketing, supply chain, finance, and manufacturing, all driven by our vision to "Build AI Together and Beyond."Here are some of the credits that MoBagel has received:

  • 2024 Emerging Tech Impact Radar: Artificial Intelligence
  • 2024 Hype Cycle for Environmental Sustainability
  • 2024 Hype Cycle for Data, Analytics and AI Programs and Practices
  • 2024 Gartner’s Hype Cycle Builder in AI Innovation
  • 2023 Market Guide for Augmented Analytics
  • 2023 Hype Cycle for Environmental Sustainability
  • 2023 Hype Cycle for Data and Analytics Programs and Practices
  • 2022 Hype Cycle : AI For Sustainability
  • 2022 Emerging Tech Impact Radar: Artificial Intelligence
  • 2022 Emerging Tech Impact Radar: Robotic & Automation
  • 2022 Market Guide for Augmented Analytics
  • 2022 Market Guide for AI Startups
  • 2021 Augmented Analytics BI and Data Science Solution
  • 2020 Top10 Strategic Technology Trends - AI Democratization2019 Microsoft Accelerator (Taipei) Batch 1 Taipei Acceleration Program
  • 2019 loT World Startup Elevate Pitchoff Winner, Pitch Group 4: loT Capabilities: AI & Machine Learning and Security
  • 2016 Nokia Open Innovation Challenge 2016 (Europe)The top 3 winning teams
  • 2016 SoftBank Innovation Program 1st Round Winners, 2016 G-Startup Worldwide SV Global Final Top 15
  • 2016 Slush Asia 2016 Top 5
  • 2016 G-Startup Worldwide Beijing Top 50
  • 2014 Salesforce 1M Hackathon 6th place

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