Senior Machine Learning

hace 2 semanas

Desde casa, México AP Consulting A tiempo completo

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**Senior Machine Learning Engineer**

We have a very unique approach to helping streaming companies develop the perfect combination of a seamless journey of watching your favorite sitcom, cooking show, live sporting event, home improvement, etc with the additional benefit of actually buying using Machine Learning and Computer Vision technologies.
We're a team of entrepreneurs that have done multiple company exits from Klarna, eBay, Amazon, Warner Bros, Google.

**Position Overview**
We are looking for a Senior Machine Learning Engineer to develop and implement advanced LLM-based systems. You will work closely with a small but dynamic team of 6-8 engineers and scientists. Reporting directly to the CTO, you will play a pivotal role in designing, training, and deploying state-of-the-art language models, as well as optimizing their performance across our entire platform.

**Responsibilities**
- Fine-tune LLMs and implement Retrieval-Augmented Generation (RAG) systems to enhance model performance and knowledge
- Optimize LLM deployments for cost efficiency, including techniques such as quantization and distillation
- Prepare and clean diverse datasets for LLM training and evaluation
- Collaborate with senior business leaders on model architecture, deployment strategies,and long-term AI roadmap
- Interact directly with end-users to gather requirements and feedback on LLM system performance

**Qualifications**
- 5+ years of experience in machine learning engineering, with a focus on natural language processing and multi-modal LLMs
- Proficiency with Python and deep learning frameworks such as PyTorch or TensorFlow
- Strong background in data preprocessing and feature engineering for NLP tasks
- Solid problem solving and system design skills
- Hands-on experience with fine-tuning LLMs and implementing Retrieval-AugmentedGeneration (RAG) systems
- Experience deploying and monitoring machine learning models on cloud platforms, preferably AWS
- Startup mentality to iterate rapidly, work across disciplines, and focus on customers

**Preferred qualifications**
- Experience with AWS SageMaker or GCP Vertex AI for model training, deployment, and management
- Proficiency using infrastructure-as-code tools like AWS CDK or Terraform for ML model deployments
- Hands-on experience using LLMs for data cleaning, enrichment, and augmentation tasks
- Familiarity with ML dataset annotation tools and processes, such as AWS SageMakerGroundTruth
- Experience with prompt engineering and few-shot learning techniques for LLMs
- Knowledge of efficient training techniques like parameter-efficient fine-tuning (PEFT) orLoRA
- Familiarity with model evaluation metrics and A/B testing for LLM performance

**Benefits and Perks**
- Legal benefits
- 100% Remote Work Scheme
- Additional days off after 3 months
- Major Medical Expenses Insurance including direct family members
- Funeral Expenses Insurance.
- Loyalty bonus for an additional 15 days
- Flexible working hours
- 4% Savings Fund
- Profit Sharing.
- Training Programs
- English classes
- Work tool

**Job Types**: Full-time, Permanent

Pay: Up to $80,000.00 per month

**Experience**:

- AWS: 2 years (required)
- Python: 5 years (required)
- Machine Learning: 3 years (required)
- Deep Learning: 2 years (required)

**Language**:

- Inglés (required)

Work Location: Remote

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