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Lead Machine Learning Engineer
Thoughtworks — престижная консалтинговая компания с сильной инженерной культурой. Позиция предлагает высокий уровень автономии, работу с современным стеком и возможности для профессионального роста.
Сложность вакансии
Роль требует не только глубоких технических знаний в ML и MLOps, но и развитых лидерских качеств для управления проектами и менторства. Дополнительную сложность создает требование к гражданству или PR Сингапура.
Анализ зарплаты
Зарплата для Lead ML инженеров в Сингапуре обычно выше среднего по рынку из-за высокой стоимости жизни и дефицита квалифицированных кадров. Указанный диапазон соответствует уровню крупных технологических компаний и международных консалтинговых агентств в регионе.
Сопроводительное письмо
I am writing to express my strong interest in the Lead Machine Learning Engineer position at Thoughtworks. With extensive experience in designing end-to-end scalable ML systems and a deep commitment to MLOps excellence, I am confident in my ability to drive technical strategy and deliver high-stakes projects for your clients. My background in Python, distributed systems, and cloud platforms like AWS and GCP aligns perfectly with the technical requirements of this role.
Throughout my career, I have balanced hands-on coding with strategic leadership, mentoring cross-functional teams to achieve technical excellence. I am particularly drawn to Thoughtworks' culture of continuous learning and your focus on Responsible AI. As a Singaporean citizen/PR, I am ready to contribute to your Singapore team and help navigate intricate technical challenges while fostering a collaborative environment for innovation.
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Описание вакансии
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.
Due to the project requirement, candidates must be Singaporean citizens or already hold Singaporean Permanent Residency (PR) at the time of application.
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.
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-Onsite
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Навыки
- AWS
- Azure
- Python
- GCP
- PyTorch
- CI/CD
- MLOps
- Scikit-learn
- Infrastructure as Code
- Distributed Systems
- Databricks
- TensorFlow
- Kubeflow
- MLflow
- Shell
Возможные вопросы на собеседовании
Проверка опыта в проектировании архитектуры для крупных систем.
Опишите ваш опыт проектирования масштабируемой ML-инфраструктуры для обработки данных в реальном времени. Какие компромиссы вы учитывали?
Оценка навыков лидерства и управления изменениями.
Как вы внедряли культуру MLOps или Responsible AI в команде, которая ранее не использовала эти подходы?
Проверка умения работать с клиентами и бизнесом.
Расскажите о случае, когда технические ограничения проекта конфликтовали с бизнес-целями клиента. Как вы разрешили эту ситуацию?
Оценка технической экспертизы в современных фреймворках.
В каких ситуациях вы бы предпочли использование Kubeflow вместо управляемых сервисов (например, SageMaker), и наоборот?
Проверка навыков менторства.
Как вы подходите к профессиональному развитию младших инженеров в вашей команде, сохраняя при этом темп разработки проекта?
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