Offer summary

Qualifications:

Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related field., At least 5 years of hands-on experience with machine learning tools and techniques., Proficiency in AWS services, particularly SageMaker, TensorFlow, and PyTorch., Excellent verbal and written communication skills..

Key responsabilities:

Deliver machine learning solutions on AWS in collaboration with the team.

Lead engineers in building solutions and decompose business goals into actionable tasks.

Design and document ML models, MLOps, and analytics while integrating with AWS AI/ML services.

Monitor and improve model performance, automating tasks using MLOps tools.

Job description

Company Overview: Avahi is a trusted AWS partner that helps businesses transform their operations with cloud-based solutions. We are a dynamic and rapidly growing company known for its vibrant culture and innovative approach. As an emerging player in the industry, we thrive on challenges and seek individuals who are enthusiastic about contributing to our exciting startup journey. We are on the lookout for motivated go-getters who are ready to make a significant impact and be part of a team that values collaboration, creativity, and continuous learning.

Position: Machine Learning Engineer

Location: Mexico (remote)

Job Type: Full-Time

About the Role:

We are seeking an experienced and highly motivated Machine Learning Engineer to join our dynamic team. The ideal candidate will have a strong background in cloud data technologies, particularly within the AWS ecosystem, and possess the skills necessary to design, implement, and maintain robust ML solutions. At Avahi, we provide solutions for some of the most complex data engineering, machine learning, and artificial intelligence projects. Our mission is to treat people with kindness and deliver exceptional, world-class engineering services

Responsibilities

Work with our team to deliver machine learning solutions on AWS
Decompose business goals into architecture and Sprint-level tasks
Having had thorough hands on experience, lead engineers in building solutions
Participate in daily standup meetings and address technical issues
Design and document ML models, MLOps, and analytics
Big data processing and preparation of training data for models
Integration with AWS AI/ML services (Comprehend, Rekognition, Transcribe)

Requirements

Excellent verbal and written communication is a minimum requirement
At least 5 years of hands on experience in most of these ML tools/techniques:
Build ML models in SageMaker
Build MLOps pipelines in SageMaker and/or MLflow
Build ML models in frameworks like Tensorflow & PyTorch and deploy in SageMaker
Train and deploy AWS pre-trained AI Services and Foundational Models
Build and optimize ML models
Familiarity with Large Language Models (LLMs) and Hugging Face integrations with AWS SageMaker
Familiarity with Retrieval Augmentment Generation
Integrate ML models into real-time applications and batch workflows
Infrastructure design and optimization
Monitor, evaluate and continuously improve model performance, as well as automate these tasks using one or more tools for MLOps
Understanding of Vector database offerings on AWS
Understanding of Multi-task Language Understanding MMLU
Data integration, cleansing, transformation, and visualization using Python packages, SQL etc.
AWS services such as Glue, EMR, Athena, DynamoDB, StepFunctions, EKS etc
Experience with an IaC tool such as CloudFormation, CDK or Terraform

Education:

Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related field. Relevant certifications in AWS or cloud technologies are a plus.

Benefits

Why Avahi:

Join a dynamic startup environment with a strong emphasis on innovation and collaboration.
Make a meaningful impact on the company's growth and technical direction.
Work with a team of highly skilled professionals who are passionate about technology.
Competitive compensation package, including salary, benefits, and opportunities for career advancement.