Generative AI Engineer
- Full Time
- Montreal, QC
Job title: Generative AI Engineer
Company: Alexa Translations
Job description: About Alexa Translations
Alexa Translations provides translation services in the legal, financial, and securities sectors by leveraging proprietary A.I. technology and a team of highly specialized linguistic experts. Unmatched in speed and quality, our machine translation engine is best-in-class and specifically trained for the French-Canadian market. If that wasn’t enough, our technology is backed by two decades of award-winning client service.About the Role
We are looking for a Generative AI Engineer to develop our next-generation intelligent translation and translation-related service engine, using Generative AI (GenAI) and Large Language Model (LLM) technologies. You will report to the team lead on GenAI, develop and implement state-of-the-art algorithms by fast prototyping, and collaborate with the software team to deploy models. We expect our Generative AI Engineer to stay current with the technological cutting edge and build applications of LLM and GenAI to machine translation with best industry practices, as well as having solid background and hands-on experience with deep learning, machine learning, natural language processing, and big data.Responsibilities
● Research and implement state-of-the-art LLM techniques including continued pre-training, instruction fine-
tuning, preference alignment, and LLM deployment while also focusing on prompt engineering and GenAI more
broadly.
● Work closely with machine learning engineers and data scientists to design, build, and test models.
● Contribute to technological innovations by staying current to the cutting-edge achievements of GenAI and LLM
from industry and academia.
● Develop efficient and scalable algorithms for training and inference of generative models, leveraging deep
learning frameworks such as TensorFlow or PyTorch and optimizing performance on diverse hardware platforms.
● Train and evaluate generative models using appropriate metrics and benchmarks, fine-tuning model parameters, architectures, and hyperparameters to optimize performance, stability, and generalization.
● Work closely with software and DevOps engineers to deploy GenAI models.
● Document code, algorithms, and experimental results, following best practices for reproducibility, version
control, and software engineering, and contribute to internal knowledge sharing and continuous improvement
initiatives.Requirements
● Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, or related field.
● 1+ years of industry experience developing GenAI and LLM applications is preferred.
● Proficiency in Python programming and software development practices, with experience in building and
maintaining scalable, production-grade software systems.
● Working knowledge and project-based record of all of the following: prompt tuning, RAG, ICL.
● Working knowledge and project-based record of at least one of the following is a plus: continued pre-training,
instruction fine-tuning, Agent.
● Strong problem-solving skills, attention to detail, and the ability to work independently and collaboratively in
a fast-paced environment.
● Hands-on experience with Huggingface APIs or Amazon Bedrock.
● Expert skills of Python, including PyTorch, TensorFlow, Pandas, etc.
● Experience with cloud platforms like AWS, GCP, or Azure
● Self-driven, self-motivated with excellent time management skills
● Excellent communication skills, with the ability to convey complex technical concepts clearly and effectively to
both technical and non-technical stakeholders.
● Familiarity with GPU programming and optimization techniques for accelerating deep learning computations.
● Ability to adapt to shifting priorities without compromising deadlines and momentum.
● Prior experience in generative AI research, projects, or internships, with contributions to open-source projects
or publications in relevant conferences or journals.Powered by JazzHR
Expected salary:
Location: Montreal, QC
Job date: Wed, 21 Aug 2024 23:07:52 GMT
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