ML Engineer - Remote (Latin America)

Reflow

Job Overview

Location

Indiana, USA

Job Type

Full-time

Full Job Description

📋 Description

• Join Reflow as a pivotal ML Engineer, a fully remote role open to talent across Latin America, and become instrumental in shaping the future of workforce and workflow intelligence. At Reflow, we are dedicated to building a sophisticated platform that empowers teams to deeply understand and significantly enhance how work is accomplished. Our innovative approach is powered by a rapidly expanding suite of advanced machine learning models, meticulously designed to learn from the intricate patterns of real-world work. These models are the engine that drives our ability to predict outcomes with remarkable accuracy, surface critical insights that were previously hidden, and enable intelligent automation that streamlines operations.
• In this dynamic role, you will be at the forefront of developing and deploying cutting-edge machine learning solutions. Your primary responsibility will involve the comprehensive lifecycle management of our ML models. This includes the rigorous training, meticulous fine-tuning, and thorough evaluation of machine learning models utilizing diverse, real-world workflow and behavioral data. You will be tasked with constructing robust predictive models that forecast task outcomes, identify emerging productivity trends, enable accurate capacity forecasting, and drive significant improvements in workflow optimization. This is a hands-on role where you will directly contribute to the intelligence that underpins our platform.
• A significant aspect of your work will focus on the advanced fine-tuning of large models and foundation models. You will adapt these powerful pre-trained models for domain-specific applications, excelling in prediction tasks, classification challenges, and the generation of high-quality embeddings. This requires a deep understanding of model architectures and the nuances of adapting them to specific business contexts. You will also be responsible for the design and ongoing maintenance of robust feature pipelines, ensuring the efficient and reliable flow of data for model training. Furthermore, you will develop and manage sophisticated training loops, implementing best practices for model development, and establish comprehensive evaluation frameworks to rigorously assess model performance before deployment.
• Collaboration is key to our success. You will work in close partnership with our talented software engineers and product teams, ensuring seamless integration of the trained models into our production systems. This involves understanding the technical constraints and opportunities within our platform and translating ML capabilities into tangible product features. Post-deployment, your role continues as you will actively monitor the performance of our models in live environments, utilizing both offline evaluation techniques and real-time data feedback to identify areas for improvement. This iterative process of monitoring, analysis, and refinement is crucial for maintaining and enhancing the accuracy and effectiveness of our ML-driven insights.
• This is an exceptional opportunity to build the core learning engine of Reflow. You will transform raw work data into actionable predictions and valuable signals that directly impact how businesses operate. You will have the unique chance to work closely with our founders, a dedicated team of engineers, and product visionaries, contributing directly to the strategic direction of the company. The role offers the ability to ship real models into production rapidly and witness firsthand how they shape the way teams work and collaborate. We foster a flexible work structure, accommodating both part-time and full-time commitments, with a strong emphasis on individual ownership, autonomy, and a rapid iteration speed that allows for continuous innovation and improvement. If you are passionate about applying ML to solve complex real-world problems and thrive in a fast-paced, collaborative environment, this is the role for you.

🎯 Requirements

• Strong foundational knowledge and practical experience in Python programming and applied machine learning principles.
• Proven experience in training and evaluating both supervised and self-supervised machine learning models.
• Hands-on experience with the end-to-end machine learning workflow, including model fine-tuning, evaluation, and deployment strategies.
• Demonstrated ability to work across the entire ML lifecycle, from raw data exploration and preparation through model training to production inference.
• A pragmatic, curious, and experimental mindset with a clear bias towards developing and shipping functional, impactful models.
• Bonus: Experience fine-tuning large language models (LLMs) or embedding models.
• Bonus: Familiarity with deep learning frameworks such as PyTorch, TensorFlow, or similar.
• Bonus: Background in time series forecasting, behavioral modeling, or graph-based learning techniques.
• Bonus: Prior experience working with messy, real-world product data and deriving insights from it.

🏖️ Benefits

• Opportunity to build the core learning backbone of Reflow, directly impacting the platform's intelligence and predictive capabilities.
• Close collaboration with founders, experienced engineers, and product teams, fostering a dynamic and innovative work environment.
• Ability to ship real models into production and see their direct impact on how teams work and improve their productivity.
• Flexible work structure, supporting both part-time and full-time engagement to suit individual needs.
• A culture that emphasizes ownership, autonomy, and rapid iteration speed, allowing for significant professional growth and impact.
• Fully remote position with the flexibility to work from anywhere within Latin America.

Skills & Technologies

Python

TensorFlow

PyTorch

Data Science

Remote

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Reflow

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About Reflow

Reflow is a cloud-based platform designed to automate and streamline the process of software updates for IoT devices. It provides a secure and reliable solution for managing firmware over-the-air (FOTA) deployments, enabling companies to efficiently deliver updates, patches, and new features to their connected products. The platform offers features such as staged rollouts, rollback capabilities, and detailed monitoring to ensure smooth and successful updates. Reflow aims to reduce the complexity and risk associated with device management, allowing manufacturers to maintain product security, enhance user experience, and extend the lifespan of their IoT ecosystems without manual intervention.

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