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Senior Machine Learning Engineer
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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 OnlyPrincipales responsabilidades:
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Analizar requerimientos de negocio y traducirlos en diseños de arquitectura de datos de alto y bajo nivel.
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Diseñar y desplegar productos de datos alineados a estándares del Banco y buenas prácticas de arquitectura.
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Definir arquitecturas eficientes para entornos On‑Premise y Cloud Big Data, asegurando performance y escalabilidad.
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Implementar soluciones basadas en eventos, colas, streaming y procesamiento distribuido.
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Establecer estándares y líneas base de diseño que soporten la estrategia de datos institucional.
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Aplicar estrategias de testing orientado a datos para validar criterios de aceptación.
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Proponer iniciativas de mejora continua para productos, procesos y habilitantes tecnológicos.
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Comunicar conceptos técnicos de arquitectura de datos a stakeholders no técnicos.
Requerimientos:
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Más de 5 años de experiencia en Arquitectura de Datos en entornos complejos.
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Experiencia sólida en Big Data y arquitecturas Cloud.
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Dominio de eventos, colas, streaming y Apache Spark (incluyendo optimización).
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Experiencia con Data Products, Data Mesh y Data Governance.
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Conocimiento avanzado en modelado de datos SQL y NoSQL.
- Experiencia en DataOps y/o MLOps.Manejo de PySpark y Scala.Experiencia en el sector financiero/bancario.
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Inglés nivel intermedio.
Ofrecemos:
- Contratación a tiempo indeterminado (relación de dependencia)
- Beneficios de Ley (Afiliación a la seguridad social, 10° tercero, 10° cuarto, despensas y utilidades)
Seguro médico privado (BMI) - Póliza de vida (BMI)
- Día libre de Cumpleaños
Te invitamos a conocernos en http://www.neoris.com, Facebook, LinkedIn, Twitter o Instagram: @NEORIS.
Patricio Albornoz C.
#LI-PA1
Ready to apply?
Apply to NEORIS
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