Key Facts

Remote From:

Latin America

Full time

Senior (5-10 years)

English

Hard Skills

Other Skills

•
Collaboration
•
Communication
•
Teamwork
•
Analytical Thinking
•
Mentorship
•
Problem Solving

Roles & Responsibilities

5+ years of industry experience in Computer Vision and applied Machine Learning
3+ years experience in building, deploying, and managing machine learning and deep learning models in production environments at scale
Deep understanding of Computer Vision and ML algorithms/techniques (CNNs, transformers, GANs, optimizers, regularization) and experiment design and best practices (A/B testing, training/serving pipelines, feature engineering)
Extensive experience with Python scientific libraries (numpy, pandas) and ML frameworks (PyTorch, TensorFlow, Keras, Scikit-Learn)

Requirements:

Develop and deploy Computer Vision and Machine Learning solutions to solve business problems
Maintain clean, efficient, and scalable code that meets industry standards
Analyze large datasets to extract actionable insights and make informed decisions
Mentor other team members to help establish team domain expertise

NIR-YU

Human Resources, Staffing & Recruiting

About NIR-YU

Nir-Yu specializes in helping Small and Medium Enterprises unlock the potential of their business. Our typical customer is worried about not being able to make enough progress on their product(s) or project(s) with their current team; they need additional team-members to deliver work on-time and with the required quality. Tight budgets also make it necessary to lower average wage costs, making it necessary to consider hiring internationally to lower costs. We help these companies by providing a bespoke service that finds and hires remote workers from Mexico, Colombia, Argentina, Chile, Brazil and other countries in LatAm based on the company’s specific job descriptions to work as an extension of their team and perform the required functions. Unlike many other companies, we don’t have a bench of contractors to be hired out, instead each team is hired specifically to meet specific requirements and to work exclusively as a remote employee.

Company type: Scaleup

Industry: Human Resources, Staffing & Recruiting

Founded: 2018

Company size: 201 - 500

Website LinkedIn See all jobs →

Job description

The Role:

The Inbound team develops highly-scalable solutions to determine item attribute values (e.g., color, material, style) and to verify merchandise authenticity. Senior Applied Scientists own the development and deployment of machine learning solutions and influence the technical direction of their team. They will work closely with tech-leads, Product and Engineering partners in the development of the solution.

Responsibilities:

Develop and deploy Computer Vision and Machine Learning solutions to solve business problems.
Maintain clean, efficient, and scalable code that meets industry standards
Analyze large datasets to extract actionable insights and make informed decisions.
Employ state-of-the-art Machine Learning methodologies and frameworks to develop robust and scalable models.
Influence technical direction and take ownership of key components of systems and solutions, ensuring that they meet the needs of the business.
Collaborate with key stakeholders in the development of data-driven solutions and deployable products.
Mentor other team members to help establish team domain expertise.
Contribute to the company's intellectual property and technical leadership through patents and publications at top-tier conferences and journals.

Minimum Requirements:

5+ years of industry experience in Computer Vision and applied Machine Learning
Masters Degree or PhD in CS / ML, statistics, or related field, or 8+ years of industry experience.
3+ years experience in building, deploying, and managing machine learning and deep learning models in production environments at scale
Deep understanding of Computer Vision and ML algorithms/techniques (CNNs, transformers, GANs, optimizers, regularization) and experiment design and best practices (A/B testing, training/serving pipelines, feature engineering).
Extensive experience in scientific libraries in Python (numpy, pandas) and Machine Learning tools and frameworks (PyTorch, Tensorflow, Keras, Scikit-Learn)
Strong data engineering skills and experience working with large scale datasets
Experience with experiment automation frameworks (Ray Tune, W&B, Kubeflow)
Experience with cloud technologies AWS, GCP or Azure
Fluency in Python

Preferred Requirements:

PhD preferred (CS, ML, AI, Stats, OR or related field)
Background in applying ML techniques to solve real-world business problems in the retail sector.
Familiarity with MLOps tools and pipelines.
Impact-focused and passionate about delivering high-quality models