Software Engineer - Machine Learning

1 Year ago • All levels

Job Summary

Job Description

Machine Learning Engineer with Python, FastAPI, NLP, deep learning, big data technologies & AWS for gaming search engine.
Must have:
  • Machine Learning
  • Python, FastAPI
  • NLP, Deep Learning
  • Big Data Technologies
Good to have:
  • AWS Experience
  • Spark Knowledge
  • TensorFlow, PyTorch
  • NLTK, SpaCy, Gensim
Perks:
  • Startup Environment
  • Hands-On Experience

Job Details

What is Splore?


Founded and funded by Temasek and Menyala, Splore is a Human Centric AI Platform that elevates and enhances the customer and employee experience, with a focus on revenue acceleration and cost efficiency. Splore’s proprietary OS is powered by a trust-and-accuracy-focused, continually learning, multi-agent Answer Engine that can respond to complex queries and execute tasks with support for human-in-the-loop.


Splore empowers businesses to unlock the vast potential of not only their information assets but also leverage Splore's proprietary knowledge index and language models, thereby enabling them to make quicker, more informed decisions. Customers get fast, relevant, and trusted answers, thereby eliminating the all-too-common frustration of sifting through irrelevant information or waiting for answers.

Crafted by experts in machine learning, distributed systems, and enterprise applications, Splore blends data from the web with proprietary information and enterprise data to provide tailored results.


Our mission is to help elevate human experiences through empathic access to services and information.


What is the role?


We are seeking a motivated Machine Learning Engineer with proficiency in Python, FastAPI, and relevant ML libraries. The ideal candidate will have a good understanding in NLP and deep learning, knowledge of big data technologies, and familiarity with AWS. This position offers a unique opportunity to gain hands-on experience in applying machine learning techniques to real-world projects.


Responsibilities


In this role, you will:

  • Collaborate with senior engineers to develop and implement machine learning models and algorithms for our gaming search engine.
  • Assist in collecting, preprocessing, and analyzing data sets to derive meaningful insights.
  • Support the design, testing, and optimization of machine learning algorithms.
  • Participate in brainstorming sessions, contributing innovative ideas to enhance existing models or develop new ones.
  • Evaluate and select appropriate tools and technologies for machine learning projects.
  • Document research findings, methodologies, and results in a clear and structured manner.
  • Stay up-to-date with the latest advancements in machine learning and related technologies.


Attributes


We are looking for a Machine Learning Engineer with the following:

  • Dealing with Ambiguity - You thrive in navigating dynamic environments, making informed decisions amid evolving scenarios and comfortably embracing uncertainty.
  • Collaborates - We're all about teamwork here. You will work closely with the Senior Engineers to develop and implement machine learning models and algorithms. Close cross functional collaboration with our Product, Design and Engineering teams will be key in building our gaming search engine!
  • Nimble Learning - We're looking for someone who thrives in a startup environment. You're not afraid to get your hands dirty and learn through experimentation when faced with fresh challenges. You're always on the pulse of the latest ML trends and immersing yourself in new technologies.
  • Functional/ Technical Skills - Strong foundations in machine learning fundamentals and algorithms, with prior experience in developing and implementing machine learning models.
    • Proficiency in Python and FastAPI
    • Familiarity with machine learning libraries and frameworks (e.g., TensorFlow, PyTorch, scikit-learn).
    • Experience with NLP libraries/frameworks such as NLTK, SpaCy, Gensim, LLMs for NLP tasks.
    • Knowledge of big data technologies and distributed computing (e.g., Spark) and cloud platforms such as AWS is a bonus.

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