We are seeking a talented AI/ML Developer with experience in developing, deploying, and fine-tuning machine learning models using Google Cloud Platform (GCP) tools like Vertex AI. The ideal candidate has a strong foundation in machine learning and AI technologies, along with hands-on experience with cloud-based AI/ML platforms.
Key Highlights
Technical Skills Required
Benefits & Perks
Job Description
Location: Remote
Reports To: AI Product Director
Employment Type: Full Time
Our client is seeking individuals who combine excellent customer service and problem-solving
skills with the ability to function effectively both as part of a team or on an individual basis
to bring their talent to our team.
Our client is a leading global IT Solutions and Services company with over 200,000 dedicated
employees serving clients across more than 66 countries.
They offer a strong compensation package that includes competitive pay and day one benefits.
They also offer many opportunities for career advancement within an engaging and
exciting culture.
100% Remote
USC and Green Card only
No relocation
Overview:
We are looking for a talented AI/ML Developer with experience in developing,
deploying, and fine-tuning machine learning models using Google Cloud Platform
(GCP) tools like Vertex AI. This role involves working with state-of-the-art Large
Language Models (LLMs), building and maintaining RAG (Retrieval-Augmented
Generation) pipelines, and handling complex data preprocessing tasks. The ideal
candidate has a strong foundation in machine learning and AI technologies, along with
hands-on experience with cloud-based AI/ML platforms such as Vertex AI and AWS
Bedrock. You will collaborate with cross-functional teams to build scalable, high-
performance AI solutions that meet business requirements.
Key Responsibilities:
Develop, deploy, and fine-tune Large Language Models (LLMs) on platforms
like Vertex AI and AWS Bedrock.
Build, optimize, and maintain RAG (Retrieval-Augmented Generation)
pipelines to support data-driven decision-making and enhance model accuracy.
Perform complex data preprocessing, including cleaning, feature engineering,
and transformation, to prepare data for ML pipelines.
Design and implement scalable machine learning models for a variety of
business applications, focusing on NLP and generative AI.
Utilize Vertex AI, AWS Bedrock, or similar cloud-based tools to manage the
entire ML lifecycle, from model training to deployment.
Collaborate with data engineers, data scientists, and software engineers to
integrate AI/ML models into production systems.
Conduct model evaluation, A/B testing, and continuous improvement through
hyperparameter tuning and retraining.
Monitor and manage deployed models to ensure their performance, scalability,
and reliability over time.
Document technical processes, model architecture, and key decisions for
ongoing maintenance and knowledge sharing.
Qualifications:
Bachelor’s or Master’s degree in Computer Science, Data Science, Machine
Learning, or a related field.
3+ years of experience in AI/ML development, with hands-on experience in
model training, deployment, and monitoring.
Proficiency with GCP tools such as Vertex AI and familiarity with similar
platforms like AWS Bedrock for model deployment and management.
Experience in developing, fine-tuning, and deploying Large Language Models
(LLMs).
Strong understanding of NLP, deep learning frameworks (such as TensorFlow
or PyTorch), and generative AI techniques.
Solid grasp of data preprocessing techniques for structured and unstructured
data.
Proficiency in programming languages such as Python and experience with ML
libraries like scikit-learn, Hugging Face Transformers, and TensorFlow.
Skills
Experience with RAG pipelines, including building custom retrieval mechanisms
and integrating with LLMs.
Knowledge of model evaluation techniques and experience in A/B testing for
model validation.
Familiarity with cloud computing concepts and experience in deploying AI/ML
models in a cloud environment.
Hands-on experience with big data processing tools, such as Apache Beam,
Dataflow, or BigQuery.