MLOps Jobs in Lima.
All active MLOps roles based in Lima.
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Lead Machine Learning Engineer
Lead Machine Learning Engineers at Thoughtworks use modern architectures to develop end-to-end scalable machine learning systems and applications. They use their specialized depth and breadth of knowledge to impact the achievement of client, project or service objectives and advocate for ways of working to promote and deliver excellence. They operate within the framework of functional policies, navigate through intricate challenges and apply their proficiency to contribute to the success of high-stakes projects. Their leadership extends beyond technical prowess, encompassing strategic thinking and effective collaboration to drive innovation and deliver solutions that meet and exceed organizational goals.
As a lead machine learning engineer on projects, you will be leading the design of technical solutions or perhaps overseeing a program inception to build a new system and/or application. Alongside hands-on coding, as a key influencer, you will shape the trajectory of machine learning engineering initiatives, playing a pivotal role in advancing the field and ensuring impactful outcomes for the broader objectives of the company.
Job responsibilities
- You will embrace a strategic mindset, contributing to the direction of machine learning (ML) initiatives and aligning technical solutions with broader organizational goals
- You will play a pivotal role in program inception, shaping the development of new systems and applications from idea to reality, overseeing technical feasibility and resource allocation
- You will leverage your deep understanding of modern architectures to lead the development of scalable and maintainable ML systems, ensuring optimal performance and efficiency
- You will translate client needs into technically feasible and impactful ML applications, driving solution design and deployment within complex, high-stakes projects
- You will own the development and maintenance of ML applications, including ML pipelines, model training and deployment, and monitoring and evaluation
- As a key influencer, you will champion Responsible AI and effective ways of working within the team, advocating for a culture of excellence and continuous improvement
- You will navigate intricate technical challenges with proficiency, employing your specialized knowledge to troubleshoot issues and guide the team towards successful resolutions
- You will stay at the forefront of the evolving field of machine learning, actively seeking out and implementing new technologies and advancements to ensure Thoughtworks remains a leader in innovation
- You will foster a collaborative environment, effectively leading your team through hands-on coding alongside mentorship and guidance, empowering individual growth and knowledge sharing
- You will measure and analyze the impact of ML initiatives, iteratively refining approaches and ensuring solutions deliver tangible value to clients and the organization
Job qualifications
Technical Skills
- You have experience in developing a technical vision and strategy, keeping it relevant and aligned to the business needs
- You can design and execute cross-functional requirements based on business priorities
- You have experience in writing clean, maintainable and testable code, demonstrating attention to refactoring and readability of the code using Python or Shell
- You have experience with distributed systems and scalable architectures to handle large-scale ML applications
- You have experience with building, deploying and maintaining ML systems using relevant ML techniques and platforms, i.e.: Scikit-learn, Tensorflow, MLFlow, Kubeflow, Pytorch
- You have experience with building, deploying and maintaining ML systems and experience with application of MLOps principles and CI/CD to ML
- You have experience in machine learning engineering and data science, are familiar with key ML concepts, algorithms and frameworks, and understand ML model lifecycles
- You have experience with designing and operating the infrastructure required to run different types of ML training and serving workloads, i.e.: on-premise vs. cloud infrastructure, infrastructure as code, monitoring, etc.
- You have hands-on experience with on-premise and cloud services for building and deploying ML pipelines, i.e.: Azure, AWS, GCP or Databricks and associated ML managed services
Professional Skills
- You understand the importance of stakeholder management and can easily liaise between clients and other key stakeholders throughout projects, ensuring buy-in and gaining trust along the way
- You are resilient in ambiguous situations and can adapt your role to approach challenges from multiple perspectives
- You don’t shy away from risks or conflicts, instead you take them on and skillfully manage them
- You are eager to coach, mentor and motivate others and you aspire to influence teammates to take positive action and accountability for their work
- You enjoy influencing others and always advocate for technical excellence while being open to change when needed
- You are a proven leader with a track record of encouraging teammates in their professional development and relationships
- Cultivating strong partnerships comes naturally to you; You understand the importance of relationship building and how it can bring new opportunities to our business
Other things to know
Learning & Development
There is no one-size-fits-all career path at Thoughtworks: however you want to develop your career is entirely up to you. But we also balance autonomy with the strength of our cultivation culture. This means your career is supported by interactive tools, numerous development programs and teammates who want to help you grow. We see value in helping each other be our best and that extends to empowering our employees in their career journeys.
Travel
While we’ve traditionally been a traveling consultancy, we have adopted a hybrid working model with the majority of work being completed remotely from either home or local Thoughtworks offices. However, business travel to client locations should be expected when required by Thoughtworks or our clients’ needs.
Company Policies
We are an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity or expression, pregnancy, age, national origin, disability status, genetic information, protected veteran status, or any other characteristic protected by law.
About Thoughtworks
Thoughtworks is a global technology consultancy that integrates strategy, design and engineering to drive digital innovation. For 30+ years, our clients have trusted our autonomous teams to build solutions that look past the obvious. Here, computer science grads come together with seasoned technologists, self-taught developers, midlife career changers and more to learn from and challenge each other. Career journeys flourish with the strength of our cultivation culture, which has won numerous awards around the world.
Join Thoughtworks and thrive. Together, our extra curiosity, innovation, passion and dedication overcomes ordinary.
#LI-Remote
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Senior Machine Learning Engineers at Thoughtworks build, maintain and test the architecture and infrastructure for managing machine learning applications. They are involved in supporting and contributing to the design of the end-to-end applications and products. They are responsible for building core capabilities including technical and functional machine learning systems and applications, being the anchor for functional streams of work and are accountable for timely delivery.
As a senior machine learning engineer, you will work on the latest tools, frameworks and offerings while also being involved in enabling credible and collaborative problem solving to execute on a strategy.
Job responsibilities
- You will contribute to design and drive the development of robust scalable architectures and infrastructure for deploying and managing machine learning (ML) applications, ensuring high availability, performance and security.
- You will collaborate with data scientists and engineers to translate business needs into effective and efficient ML systems and applications.
- You will own the development and maintenance of core functionalities within ML applications, including ML pipelines, model training and deployment, and monitoring and evaluation.
- You will drive the functional stream of work by providing technical expertise, handling team discussions and ensuring timely delivery of assigned tasks.
- You will stay ahead of the curve by actively exploring and implementing the latest tools, frameworks and offerings in the ML landscape.
- You will facilitate collaborative problem solving within the team by actively listening, communicating effectively and mentoring other engineers.
- You will contribute to the development and execution of the team's overall ML strategy, aligning technical capabilities with business objectives.
- You will proactively identify and address challenges related to ML systems and applications, proposing solutions and implementing improvements.
Job qualifications
Technical Skills
- An advanced English level is required.
- You must have a strong experience with LLM and AI.
- You have experience in writing clean, maintainable and testable code, demonstrating attention to refactoring and readability of the code.
- You are proficient in scripting languages such as Python or Shell for automation and task streamlining.
- You have knowledge of distributed systems and scalable architectures to handle large-scale ML applications.
- You have experience with building, deploying, and maintaining ML systems using relevant ML techniques and platforms, i.e.: Scikit-learn, Tensorflow, MLFlow, Kubeflow, Pytorch.
- You have experience with building, deploying and maintaining ML systems and experience with application of MLOps principles and CI/CD to ML.
- You have experience in machine learning engineering and data science, are familiar with key ML concepts, algorithms and frameworks, and understand ML model lifecycles.
- You have experience with designing and operating the infrastructure required to run different types of ML training and serving workloads, i.e.: on-premise vs. cloud infrastructure, infrastructure as code, monitoring, etc.
- You have hands-on experience with on-premise and cloud services for building and deploying ML pipelines, i.e.: Azure, AWS, GCP or Databricks and associated ML managed services.
Professional Skills
- You understand the importance of stakeholder management and can easily liaise between clients and other key stakeholders throughout projects, ensuring buy-in and gaining trust along the way.
- You are resilient in ambiguous situations and can adapt your role to approach challenges from multiple perspectives.
- You don’t shy away from risks or conflicts, instead you take them on and skillfully manage them.
- You are eager to coach, mentor and motivate others and you aspire to influence teammates to take positive action and accountability for their work.
- You enjoy influencing others and always advocate for technical excellence while being open to change when needed.
Other things to know
Learning & Development
There is no one-size-fits-all career path at Thoughtworks: however you want to develop your career is entirely up to you. But we also balance autonomy with the strength of our cultivation culture. This means your career is supported by interactive tools, numerous development programs and teammates who want to help you grow. We see value in helping each other be our best and that extends to empowering our employees in their career journeys.
About Thoughtworks
Thoughtworks is a dynamic and inclusive community of bright and supportive colleagues who are revolutionizing tech. As a leading technology consultancy, we’re pushing boundaries through our purposeful and impactful work. For 30+ years, we’ve delivered extraordinary impact together with our clients by helping them solve complex business problems with technology as the differentiator. Bring your brilliant expertise and commitment for continuous learning to Thoughtworks. Together, let’s be extraordinary.
#LI-Remote
Ready to apply?
Apply to Referrals Only
Founding ML Engineer (Spectrum)
Software engineers and AI agents alike suffer from the same problem: finding that one person or place that will answer their tough, specific question. Many solutions promise to solve this with similarity search in vector databases. Unfortunately, finding the answer is often a puzzle with pieces to be collected across a myriad of contradictory sources and cannot be solved without surgical search and careful reasoning.
Spectrum collects data from an organization’s code, docs, and issues, and organizes knowledge in a unified ontology that AI agents can efficiently search through and reason over. We aim to revolutionize the semantic layer space for software-building organizations and move beyond specs that fall out of sync with code, introducing a living spec – one that’s extracted from the whole system and used to keep it aligned. Spectrum is meant to be the single source of truth for all product and architectural knowledge.
Spectrum is a resident of JetBrains' startup incubator, with startup speed and autonomy, and backed by 25 years of developer tooling expertise. We are looking for a top-class ML Engineer who will help us shape the future of software development. You will own our AI and ML engineering stack and help define the research agenda for our team. Your technical vision and design decisions will directly shape the product and determine its success.
Your responsibilities will include:
- Designing and building the ML/LLM solution for data ingestion, knowledge extraction, retrieval, and subsequent reasoning.
- Creating the datasets, metrics, and pipelines that drive measurable improvements across the system.
- Architecting and improving agents for context retrieval, knowledge extraction, and data alignment, which includes prompt engineering, model selection, and inference optimization.
- Establishing MLOps practices, including orchestration, observability, and experiment tracking.
- Collaborating with the engineering team on system design and with JetBrains Research on the research agenda.
- Defining hiring criteria, growing the ML team, and shaping the ML team culture.
We expect you to have:
- A proven track record as an ML/AI Lead.
- At least five years of experience in ML/AI systems, with at least two years focused on LLMs and generative AI.
- A deep understanding of the LLM ecosystem, including model architectures and fine-tuning approaches.
- Hands-on experience with:
- Prompt engineering and LLM pipeline design, including evaluation.
- Agentic frameworks such as LangChain, LlamaIndex, LangSmith, smolagents, or an equivalent.
- Vector databases and retrieval-augmented generation (RAG) patterns.
- Deploying and scaling LLM-powered applications using APIs (e.g. OpenAI or Anthropic) or open-source models.
- Strong Python skills – Kotlin knowledge would be a plus.
- Excellent communication skills, with the ability to explain complex technical concepts to diverse audiences.
- Proficiency in English, both written and verbal.
Our ideal candidate would have:
- Experience with ontologies, knowledge graphs, or graph-based reasoning.
- Experience in early-stage startups – you enjoy the zero-to-one phase.
- The ability to think strategically about product-led AI, beyond just training models in isolation.
- A background in code analysis, developer tools, or software engineering research.
- Experience with multi-agent systems or complex agentic workflows.
- Actively contributed to relevant open-source projects or publications.
What we offer
- A competitive salary and JetBrains benefits.
- A generous runway and corporate resources with startup autonomy.
#LI-KP1
We are an equal opportunity employer
We know great ideas can come from anyone, anywhere. That’s why we do our best to create an open and inclusive workplace – one that welcomes everyone regardless of their background, identity, religion, age, accessibility needs, or orientation.
We process the data provided in your job application in accordance with the Recruitment Privacy Policy.
Ready to apply?
Apply to JetBrains
Senior AI/ML Engineer (Spectrum)
Software engineers and AI agents alike suffer from the same problem: finding that one person or place that will answer their tough, specific question. Many solutions promise to solve this with similarity search in vector databases. Unfortunately, finding the answer is often a puzzle with pieces to be collected across a myriad of contradictory sources and cannot be solved without surgical search and careful reasoning.
Spectrum collects data from an organization's code, docs, and issues, and organizes knowledge in a unified ontology that AI agents can efficiently search through and reason over. We aim to revolutionize the semantic layer space for software-building organizations and move beyond specs that fall out of sync with code, introducing a living spec – one that's extracted from the whole system and used to keep it aligned. Spectrum is meant to be the single source of truth for all product and architectural knowledge.
A resident of JetBrains' startup incubator, Spectrum enjoys startup speed and autonomy, and is backed by 25 years of developer tooling expertise. We are looking for a Senior AI/ML Engineer to build and evolve the ML-powered systems at the heart of our product.
Your responsibilities will include:
- Designing and building the ML/LLM solution for data ingestion, knowledge extraction and retrieval, and subsequent reasoning.
- Creating datasets, metrics, and pipelines that drive measurable improvements across the system.
- Architecting and improving AI agents, which will involve prompt engineering, model selection, and inference optimization.
- Contributing to our MLOps practices, including orchestration, observability, and experiment tracking.
We expect you to have:
- At least four years of experience building ML/AI systems in production environments, with hands-on LLM experience.
- A deep understanding of the LLM ecosystem, including model architectures and fine-tuning approaches.
- Hands-on experience with:
- Prompt engineering and LLM pipeline design, including evaluation.
- Agentic frameworks such as LangGraph, Pydantic AI, or an equivalent.
- Retrieval-augmented generation (RAG) patterns and vector databases.
- Deploying and scaling LLM-powered applications using APIs (e.g. OpenAI or Anthropic) or open-source models.
- Strong Python skills – Kotlin knowledge would be a plus.
- Excellent communication skills, with the ability to explain complex technical concepts to diverse audiences.
- Proficiency in English, both written and verbal.
Our ideal candidate would also have:
- Experience with ontologies, knowledge graphs, or graph-based reasoning.
- Experience in early-stage startups – you enjoy the zero-to-one phase.
- A background in code analysis, developer tools, or software engineering research.
- Experience with multi-agent systems or complex agentic workflows.
- Actively contributed to relevant open-source projects or publications.
What we offer:
- A competitive salary and JetBrains benefits.
- A generous runway and corporate resources with startup autonomy.
- A motivated team that moves fast, with short feedback loops, rapid prototyping, and lots of ownership.
- Opportunities to publish research at top venues in collaboration with JetBrains Research.
#LI-DNI
We are an equal opportunity employer
We know great ideas can come from anyone, anywhere. That’s why we do our best to create an open and inclusive workplace – one that welcomes everyone regardless of their background, identity, religion, age, accessibility needs, or orientation.
We process the data provided in your job application in accordance with the Recruitment Privacy Policy.
Ready to apply?
Apply to JetBrains
Senior MLOps Engineer (ML Workflows Engineering)
At JetBrains, code is our passion. Ever since we started, back in 2000, we’ve been striving to make the strongest, most effective developer tools on earth. By automating routine checks and corrections, our tools speed up production, freeing developers to grow, discover, and create.
Today, AI-powered assistance and agents are becoming a core part of how developers work in our IDEs. The ML Workflows Engineering team is dedicated to removing infrastructure challenges, streamlining machine learning operations (MLOps), and enabling teams to focus on the innovative work that matters most – building impactful ML models and intelligent agents. As part of the team, you'll play a key role in designing tools, automation, and pipelines that make machine learning development seamless and intuitive.
By integrating cutting-edge MLOps practices and engineering excellence, we aim to maximize productivity and remove the complexity of ML infrastructure so that our teams can push the boundaries of what’s possible in AI.
As part of our team, you will:
- Build tools, automation, and workflows to simplify infrastructure-heavy tasks, empowering AI teams to focus on experimentation and solving core challenges.
- Develop robust monitoring, logging, and tracing systems to ensure the performance and reproducibility of ML workflows in production.
- Design, implement, and maintain end-to-end machine learning pipelines to enable the seamless development, training, and deployment of ML models and intelligent agents.
- Work with large-scale distributed systems, including GPU clusters, to support training, fine-tuning, and evaluation of ML models.
- Collaborate with product and development teams to transform high-level goals into concrete, scalable, and maintainable systems.
- Optimize workflows for reproducibility, scalability, and cost-efficiency while keeping ML teams productive and focused on innovation.
We’ll be happy to have you on our team if you have:
- Hands-on experience with modern MLOps tooling, including Kubernetes, Cloud providers (GCP and AWS), and ML orchestration frameworks.
- A solid understanding of the ML lifecycle from idea to the customer-facing application.
- The ability to own projects end to end, starting from a high-level problem or product pain point and overseeing it through the design, experimentation, implementation, and iteration phases.
- A customer-centric mindset – you care about how ML engineers are actually working and can translate their needs into actionable, scalable, and maintainable architectural decisions.
- Experience with modern CI/CD systems, like GitHub Actions or JetBrains TeamCity.
- At least three years of Python experience writing clean, maintainable code in modern ML codebases.
Our ideal candidate would have experience with:
- ML orchestrators and workflow tools such as ZenML, Dagster, and Airflow.
- Developing infrastructure components and services using cluster solutions like Kubernetes.
- The development of Python-based backend services.
- Creating and maintaining ML pipelines, including legacy ones.
- Experiment tracking and observability using tools like Weights & Biases, MLflow, Langfuse, or similar.
We’d be especially thrilled if you have experience with:
- LLM inference frameworks such as vLLM, DeepSpeed, and TensorRT.
- Writing and maintaining Python libraries used by internal (or external) ML engineers.
- A strong theoretical background in NLP and transformer-based approaches.
- Writing code in Java and/or Kotlin.
#LI-HYBRID
#LI-MR1
We are an equal opportunity employer
We know great ideas can come from anyone, anywhere. That’s why we do our best to create an open and inclusive workplace – one that welcomes everyone regardless of their background, identity, religion, age, accessibility needs, or orientation.
We process the data provided in your job application in accordance with the Recruitment Privacy Policy.
Ready to apply?
Apply to JetBrains
Staff Research Engineer (LLM Pre-Training)
At JetBrains, code is our passion. Ever since we started back in 2000, we have been striving to make the world’s most robust and effective developer tools. By automating routine checks and corrections, our tools speed up production, freeing developers to grow, discover, and create.
We are working on an ambitious new platform that provides AI capabilities to all JetBrains products. Our platform is based on models developed in-house for writing and coding assistance, as well as integration with our strategic partners.
We are looking for a Research Engineer who can contribute to training foundation models for coding tasks. You’ll be working on developing Large Language Models from scratch and deploying them into production environments where they will be accessible by end users across the globe.
We value engineers who:
- Can plan projects and make decisions independently, consulting with others if needed.
- Identify customer needs and prioritize their tasks accordingly.
- Start with the simplest solutions and gradually add complexity as needed.
- Take sole responsibility for an entire subsystem.
- Have a passion for learning and a desire to stay up to date with the latest developments in the LLM field.
In this role, you will:
- Work with stakeholders to convert business requirements into technical specifications.
- Train LLMs from scratch on a large GPU cluster.
- Collect and process pre-training and fine-tuning datasets.
- Support and improve existing subsystems.
We’ll be happy to have you on our team if you have:
- Experience in design, deployment, and support of production ML systems.
- A strong theoretical background in NLP and transformer-based approaches.
- Proficiency with modern deep learning frameworks such as PyTorch and common libraries for NLP.
- Experience in distributed training of multi-billion parameter models.
- Attention to detail in everything you do and great communication skills.
We’d be especially thrilled if you have experience with:
- LLM inference frameworks such as vLLM, DeepSpeed, TensorRT.
- LLM alignment techniques such as RLHF/RLAIF.
- MLOps tools and practices, including CI/CD for ML.
- K8s and Kubeflow.
- Scientific publications in the NLP field.
How we develop JetBrains AI:
- A cluster of hundreds of NVIDIA GPUs as training infrastructure.
- Git for source control management.
- Python, PyTorch, and HuggingFace as an ML stack.
- Kubeflow and Weights & Biases for experiment tracking.
- TeamCity as a CI Automation system.
#LI-KP1
We are an equal opportunity employer
We know great ideas can come from anyone, anywhere. That’s why we do our best to create an open and inclusive workplace – one that welcomes everyone regardless of their background, identity, religion, age, accessibility needs, or orientation.
We process the data provided in your job application in accordance with the Recruitment Privacy Policy.
Ready to apply?
Apply to JetBrains
Head of ML
At JetBrains, code is our passion. Ever since we started back in 2000, we have been striving to make the world’s most robust and effective developer tools. By automating routine checks and corrections, our tools speed up production, freeing developers to grow, discover, and create.
JetBrains is evolving beyond standalone developer tools toward a unified, AI-native platform for software development.
AI is no longer just an assistant inside the editor – it is becoming an active participant in how software is planned, built, reviewed, and operated across teams and organizations. This shift introduces new challenges that cannot be solved at the level of individual tools alone: governance, security, cost control, observability, and coordinated work between humans and autonomous agents.
Our goal is to build a platform that enables companies to adopt AI in software development in a structured, scalable, and economically efficient manner without locking them into closed ecosystems. This platform will serve as the execution and governance layer for AI-driven development, deeply integrated with developer tools but designed to work across teams, products, and environments.
We are looking for an experienced ML leader who has created products with an ML backbone, weaving together research, technical excellence, and strong product focus.
We are seeking a professional who excels in three key areas: technology, product vision, and business operations. This role involves extensive cooperation with products across the company – both AI-native and just integrating AI.
In this role, you will:
- Identify, prioritize, and champion high-impact AI projects that align with JetBrains' product strategy and deliver measurable business value.
- Lead a team of about 50 people across multiple AI initiatives, including hiring and developing team leads, ML engineers, and MLOps specialists.
- Set the technical direction for JetBrains’ ML roadmap, translating cutting-edge AI advancements into practical product innovations.
- Ensure projects deliver on commitments and create measurable value.
- Set technical standards, architectural direction, and best practices for ML development.
We’ll be happy to have you on our team if you have:
- The ability to balance long-term R&D with short-term product needs.
- A track record of shipping production ML systems that users actually use.
- Experience building business cases for technical projects.
- A deep understanding of modern ML infrastructure, LLMs, and AI tooling.
- Outstanding stakeholder management skills and are comfortable working with senior leaders.
- The ability to thrive in a fast-paced environment, effectively managing multiple projects simultaneously.
- Excellent management and communication skills.
- Attention to detail in everything you do.
We’d be especially thrilled if you have experience with:
- Distributed training of multi-billion parameter models.
- CI systems, workflow automation, and experiment tracking.
- The Kotlin programming language.
#LI-KP1 #LI-HYBRID
We are an equal opportunity employer
We know great ideas can come from anyone, anywhere. That’s why we do our best to create an open and inclusive workplace – one that welcomes everyone regardless of their background, identity, religion, age, accessibility needs, or orientation.
We process the data provided in your job application in accordance with the Recruitment Privacy Policy.
Ready to apply?
Apply to JetBrains