Senior ML/Edge Engineer (Signals) – Health Care – (LATAM/Remote)

Remote, USA Full-time
About Truelogic At Truelogic we are a leading provider of nearshore staff augmentation services headquartered in New York. For over two decades, we’ve been delivering top-tier technology solutions to companies of all sizes, from innovative startups to industry leaders, helping them achieve their digital transformation goals. Our team of 600+ highly skilled tech professionals, based in Latin America, drives digital disruption by partnering with U.S. companies on their most impactful projects. Whether collaborating with Fortune 500 giants or scaling startups, we deliver results that make a difference. By applying for this position, you’re taking the first step in joining a dynamic team that values your expertise and aspirations. We aim to align your skills with opportunities that foster exceptional career growth and success while contributing to transformative projects that shape the future. Our Client They are creating a fundamentally better healthcare experience for people with chronic health conditions and those who care for them. They make healthcare more accessible by simplifying complex care plans, connecting care teams, and meeting patients where they live. Through their conversational AI, patients use their voice to interact with a digital care companion that proactively provides medication reminders, symptom checks, behavioral nudges, and even engages in friendly conversations to ease loneliness. Job Summary We’re looking for a Senior ML/Edge Engineer to lead the development of ML models that power our physiological signal analysis. This role is ideal for someone who thrives at the intersection of machine learning, signal processing, and embedded systems — taking models from research to real-world deployment on constrained edge devices. Responsibilities Own the full ML lifecycle: data collection, cleaning, model training, evaluation, deployment. Develop and optimize models for signal processing and time-series biosignals. Refactor Python-based models into C/C++ for edge deployment. Address resource constraints: memory, threading, concurrency, power. Work closely with firmware/software teams to integrate models on-device. Ensure production success: deploy, monitor drift, iterate post-launch. Flexibility in profile fit: strong modelers with some C++, or strong C++ engineers with workable ML chops. Qualifications and Job Requirements 5+ years applied ML experience with embedded/edge deployment. Strong background in signal processing and time-series data. Proven ability to ship AI products into production, including drift monitoring. Proficiency in Python (modeling) and C/C++ (embedded deployment). Knowledge of resource-constrained systems. Excellent problem-solving and communication skills; thrive in a fast-moving startup. What We Offer 100% Remote Work: Enjoy the freedom to work from the location that helps you thrive. All it takes is a laptop and a reliable internet connection. Highly Competitive USD Pay: Earn an excellent, market-leading compensation in USD, that goes beyond typical market offerings. Paid Time Off: We value your well-being. Our paid time off policies ensure you have the chance to unwind and recharge when needed. Work with Autonomy: Enjoy the freedom to manage your time as long as the work gets done. Focus on results, not the clock. Work with Top American Companies: Grow your expertise working on innovative, high-impact projects with Industry-Leading U.S. Companies. Why You’ll Like Working Here A Culture That Values You: We prioritize well-being and work-life balance, offering engagement activities and fostering dynamic teams to ensure you thrive both personally and professionally. Diverse, Global Network: Connect with over 600 professionals in 25+ countries, expand your network, and collaborate with a multicultural team from Latin America. Team Up with Skilled Professionals: Join forces with senior talent. All of our team members are seasoned experts, ensuring you’re working with the best in your field. Apply now!
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