Machine Learning Engineer

Overview

Machine Learning Engineer (LATAM) role at Lateral Group.

About The Company

Lateral stands for technology excellence. We're a profitable, award-winning design and technology company with over 20 years of experience launching bold ventures and transforming businesses. A globally distributed team of 200+ experts united by the shared purpose: the continuous pursuit of quality. Our clients come to us for results, quality and craft — and stay because we keep raising the bar.

What sets us apart isn't just the talent of our team — it's the way we work: We Have A Bias For Action & Results. We are doers — we spot the gaps, connect the dots, anticipate what's around the corner and take action. We move fast, stay focused, and let the results speak for themselves. We Work On Time, On Budget, On Quality. Discipline is our edge — a commitment we make to each other, to our clients, and to the standards we hold ourselves to. We Care Deeply — we care about our work and about each other. Care Is A Competitive Advantage. Every detail matters. Thoughtful by default. We Do Things Right — integrity is non‑negotiable. We take pride in doing great work the right way. We Keep Improving — the best teams keep learning and iterating. We are Obsessed With Agility and aim to adapt processes to fit problems. We Take Ownership — everyone leads something here; you will have room to run with ideas and the trust to execute.

What You'll Do

• Experimentation and Optimization: parallelize and distribute work across experiment tracks; optimize model performance via hyperparameter tuning, model ensembling, or advanced training strategies; design and conduct systematic experiments to validate hypotheses and model improvements.
• Research and Development: conduct literature reviews on state-of-the-art methods in medical imaging; design and prototype novel ML models; implement architecture and training strategies; explore improvements to existing models or tasks.
• Analysis and Validation: perform statistical analysis to assess robustness and reproducibility; compare methods against baselines and benchmarks.
• Interdisciplinary Collaboration: collaborate with domain experts to define problem statements and interpret model outputs for clinical impact.

What We're Looking For

• 2+ years of hands-on experience in machine learning, including model design, training, and evaluation.
• Experience applying ML to real-world computer vision problems, including developing, deploying, and optimizing models.
• Familiarity with PyTorch or TensorFlow; ability to write clean, modular experimentation code.
• Experience running experiments, tuning models, and comparing approaches via systematic validation.
• Strong grasp of modern ML concepts: regularization, loss functions, optimization, generalization, overfitting.
• Basic data analysis skills using tools like Polars or Pandas for data manipulation and EDA.
• Understanding of statistical testing and experimental design for performance assessment.
• Curiosity about new techniques and the ability to apply ideas in production-minded ways.
• Strong communication skills to collaborate with engineers, researchers, and domain experts.

Bonus points for

• Experience with medical imaging, scientific ML, or regulated environments.
• Contributions to papers, open-source projects, or research infrastructure.
• Familiarity with explainability techniques (e.g., SHAP) and fairness/audit frameworks.
• Track record of generating novel ideas and translating them into working systems.
• Experience building ML pipelines (training, evaluation, deployment) in production, especially in AWS.

Why You'll Love Working Here

• Real Impact: meaningful products across healthcare, sustainability, and next‑gen tech.
• Remote-First, Office Friendly: work from anywhere; offices available for collaboration if convenient.
• Asynchronous collaboration, time-zone respect, focus on outcomes over hours.
• Outstanding Team: talented, generous professionals who care about craft and each other.
• Growth: opportunities to grow skills and take on greater responsibility at your own pace.
• Culture of Excellence: emphasis on doing the right thing, avoiding burnout, delivering high-quality work sustainably.
• Variety & Stability: profitable, independent, with a track record of delivering fresh challenges.

How to apply and interview process

Our hiring process is structured as a sequence of steps designed to be thorough yet respectful of candidate time. It includes: clear next steps, regular updates, and opportunities to ask questions.

Step 1: Express Your Interest — please send your resume, a short note about what excites you about this role, and links to work samples. Include specific contributions if sharing team projects. Step 2–7 outline the Talent Partner conversation, technical, client, operational interviews, references, and offer details, followed by an overall mutual fit assessment.

Step 2: Talent Partner Conversation; Step 3: Technical Interview; Step 4: Client Interview; Step 5: Operational Interview; Step 6: Reference Checks; Step 7: Offer. You will be guided through each step with preparation tips and expectations.

We review every application with care. If there's a fit, we'll reach out to schedule next steps. Join us and let's build something extraordinary.

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