Machine Learning Ops Engineer (Latam) Ai & Machine Learning • •

About the CompanyLateral 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 a 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.We do things differently at LateralOur mission is simple : design and build great products.What sets us apart isn't just the talent of our team -it'sthe 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 -not the effort -speak for themselves.We Work On Time, On Budget, On QualityDiscipline 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.

Every design, every line of code, every decision.

Thoughtful by default.We Do Things Right -Because It's the Right Thing to DoRight over easy.

Integrity isn't up for negotiation.

We hold the bar high even when no one's watching.

We take pride in doing great work the right way -not the easy way.We Keep ImprovingThe best teams keep improving and we're never done learning.We iterate.

We reflect on what's working and what's not.

Feedback fuels us, we receive it openly, and adapt quickly.

Progress over perfection.We're Obsessed With Agility, Not The Agile ManifestoWe don't chase dogma or rituals -we chase momentum.

We adapt processes to fit problems, not the other way around.We Take OwnershipEveryone leads something here.

You will have room to run with ideas, and the trust to execute.

That trust is built on how you show up : thinking things through, sweating the details, and following through.What You'll DoOur MLOps offering focuses on building and maintaining the robust infrastructure essential for our cutting-edge AI solutions.

As a ML Ops Engineer at Lateral, you will be crucial in ensuring the smooth operation and scalability of our AI initiatives through a variety of critical tasks : Infrastructure Management : You will be responsible for defining and proposing an infrastructure management stack that drives business objectives.Troubleshooting and Optimization : You will help identify and mitigate AI infrastructure issues and implement features to improve model training speed on specific hardware.Platform Evaluation and Implementation : You will evaluate and implement new AI training and development platforms.Automation and Orchestration : Your responsibilities will include automating model training and checkpointing using MLOps tools, and maintaining containerization tools (Docker, Singularity) for reproducibility.Deployment and Lifecycle Management : You will facilitate the transfer and replication of models from R&D to production environments, manage the model lifecycle, implement model tracking, and ensure infrastructure remains compatible with evolving training packages (e.g., CUDA, PyTorch, drivers).

This includes proactively updating packages and resolving compatibility issues to avoid regressions in training workflows.What We're Looking ForWe're seeking pragmatic infrastructure engineers who love solving deep tech problems and enabling great ML work.

You'll thrive in this role if you bring : 5+ years of hands-on experience with ML Ops tools such as SLURM, MLflow, Kubeflow, SageMaker, or Vertex AI.Experience managing Kubernetes clusters and distributed training workloads at scale.Proficiency with containerization (Docker, Singularity) and reproducible ML environments.Familiarity with popular deep learning frameworks (PyTorch, TensorFlow) and how they operate at infra level.Solid understanding of model lifecycle best practices (training, validation, deployment, tracking).

Strong scripting and automation skills in Python, Bash, or similar.Comfort working closely with ML researchers to translate needs into scalable, production-grade systems.A proactive mindset : you're excited to take ownership of infra problems others avoid.Bonus points for : Experience with multi-node, hardware-optimized training setups (e.g. GPU clusters, TPUs).

Contributions to internal tools or open-source projects in the ML Infra space.Prior experience helping bring ML systems through regulatory, safety, or quality review stages.Why You'll Love Working HereReal Impact : You'll work on meaningful products that make a measurable difference - from healthcare and commerce to sustainability and next-gen tech.Remote-First, Office Friendly : Work from wherever you're most productive - whether that's your home, a co-working space, or one of our offices.

We're a remote-first company, but if you're near an office, you're welcome to drop in, collaborate in person, or work onsite regularly.We prioritize async collaboration, respect your time zone, and focus on outcomes over hours.An Outstanding Team : Talented, kind, and hard-working people who care deeply about their craft - and about each other.

No egos.

No politics.

Just professionals doing their best work.Growth : You'll be supported in growing your craft, exploring new paths, and stepping into greater responsibility -at your own paceA Culture of Excellence : We care deeply about doing the right thing -for our clients, our team, and ourselves.

No burnout.

No crunch.

Just high-quality work, delivered sustainably.Variety & Stability : We're profitable, independent, and over a decade strong.

Yet every project brings a fresh challenge.

You'll never be bored here.This Role Might Not Be for YouWe want to respect your time by being clear about what this role isn't.

You should skip this opportunity if : You prefer well defined structure.If you gravitate towards a clear hierarchy, well defined roles and swim lanes, you may find our self-managed style challenging.Distributed work isn't your thing.If you find async communication, design documentation and being proactive without a manager nearby difficult, our setup won't suit you.Feedback doesn't excite you.We're obsessed with quality and believe in continuous improvement.

That means we give feedback that's sometimes nitpicky.

If refining the work until it's excellent feels over the top, you are likely going to find working here frustrating.Change makes you uncomfortable.We're scaling and maturing.

That means not everything is perfect yet.

Priorities shift.

Processes evolve.

If ambiguity is uncomfortable, this may feel bumpy.However, If this sounds like fuel, we'd love to talk!

How to apply and what to expect in the interview processOur hiring process is structured as a sequence of steps.

Moving forward is based on how well the previous step goes.

This helps us stay focused, fair, and respectful of everyone's time.We will always : Let you know clearly what the next step isShare updates and feedback wherever possibleInvite questions if anything feels unclearNot everyone progresses through every stage.

That doesn't mean you're not great at what you do.

Sometimes it's about timing, team fit, or simply what we're looking for at the moment.Step 1 : Express Your InterestIf this sounds like your kind of team and you're ready to bring your craft to Lateral, we want to hear from you.Please send us : YourresumeAshort noteabout what excites you about this roleLinks to your work : GitHub / Code snippets, portfolio, architecture / design docs, blog posts, oranything that shows us how you think and buildPlease don't include anything sensitive or proprietary.If you're sharing team projects, let us know what your specific contributions were.We review every application with care.

If there's a fit, we'll reach out to schedule next steps.Step 2 : Talent Partner ConversationPurpose : A structured discussion with our People Experience team to delve into your career trajectory, motivations, and alignment with Lateral's values.What to Expect : In-depth questions about your past experiences and decision-making processes.Exploration of your career goals and how they align with the role.Discussion about our company culture, availability, compensation and other logisticsMotivators and demotivators.Your life outside coding.Preparation Tips : Reflect on your career journey and pivotal moments.Be ready to discuss challenges you've overcome and lessons learned.Familiarize yourself with the Job Description, Lateral's mission and values.Step 3 : Technical interviewPurpose : Assess your technical proficiency and problem-solving abilities.Format : A collaborative session with our engineering team, focusing on real-world scenarios relevant to the role.What to Expect : Problem-solving exercises / questions that mirror tasks you'd encounter in the position.Discussions around your approach, reasoning, and solutions.Preparation Tips : Practice articulating your thought process clearly and concisely.Be prepared to discuss in depth past projects and the technologies used.Step 4 : Client interviewPurpose : Evaluate how well you collaborate, communicate, and consult with external stakeholders.Format : A live conversation with one of our client-side collaboratorsWhat to Expect : Discussion around business and technical challenges from the client's perspective.Opportunity to explain your approach, gather requirements, ask clarifying questions, and articulate tradeoffs.Evaluation of how clearly you communicate solutions to both technical and non-technical stakeholders.Preparation Tips : Once client details are shared, educate yourself with their business and potential challengesReview past experiences where you've had to communicate complex ideas clearly.Reflect on your ability to lead conversations, guide decision-making, and build trust across different audiences.Step 5 : Operational interviewPurpose : Understand your approach to prioritizing, collaborating, shipping, and iterating.What to expect : How you prioritize and break down work.How you collaborate across disciplines.How you handle blockers, feedback, and iteration.Preparation Tips : Pick 1-2 meaningful projects you led or heavily contributed to.Walk through your process : what worked, what didn't, what you'd do differently.Think about how you manage time, scope, and changing requirements.Step 6 : Reference ChecksPurpose : We believe references are about understanding, not just validation.

We do not look for perfection, but to understand patterns, strengths, and context.

We use them to learn how to support you best.What to Expect : we'll ask you for 2–3 people who've worked closely with you.

These are often : former managers, senior peers or collaborators, mentors or people you've mentored.What we ask : We focus on how you've grown, where you shine, how you like to be led, and what support sets you up for success.

We want practical advice for making this a great fit for you.Yes, we do backchannels too : We do thiswhen we feel we need more context.

We will check with you if there are folks we should avoid reaching out due to confidentiality or other reasons.

Andhere's our commitment : if anything surprising or unclear comes up in a backchannel, we'll bring it directly to you.

We believe in "no stories without you in the room."

You'll always get the chance to share your side, context, or clarification.Step 7 : OfferWhat Happens : If selected, you'll receive a comprehensive offer detailing compensation, and other pertinent information.Our hiring process is designed to be thorough yet respectful, ensuring a mutual fit.

We encourage candidates to engage actively, ask questions, and view this as a two-way exploration.Join us and let's build something extraordinary.

#J-

• Ljbffr