• Implement, validate, and iterate on machine learning algorithms for weld perception tasks, including point cloud registration, seam detection, and joint geometry estimation, progressively expanding coverage across joint types and part geometries. • Build and maintain data pipelines for training and evaluating perception models, spanning annotated 3D scan data ingestion, synthetic data generation, and structured dataset management for iterative model improvement. • Run rigorous model evaluation experiments, including failure mode analysis, FP/FN rate characterization, and benchmarking against quantitative registration accuracy thresholds, and communicate findings clearly to guide next steps. • Integrate trained models into production ROS-based robotics services, ensuring low-latency inference and compatibility with deployed cell configurations. • Write clean, well-tested Python code; participate actively in code and experiment reviews; and maintain clear documentation of methods, parameters, and results. • Lead research, development, and production deployment of advanced perception algorithms spanning point cloud registration, seam detection, and real-time in-process tracking across structured light, RGB, and stereo sensors. • Design and lead experiments evaluating state-of-the-art deep learning models, including transformer-based and geometric feature learning architectures. • Design and lead real-time perception systems such as during-weld seam tracking, applying sensor fusion with probabilistic state estimation (e.g., Kalman filtering) to achieve robust weld performance. • Define and own the end-to-end ML lifecycle, from dataset design and annotation strategy through training, benchmarking, and fleet deployment, with clear go/no-go evaluation frameworks. • Architect distributed training and hyperparameter optimization workflows; drive strategy for data acquisition, annotation tooling, and synthetic vs. real scan data usage. • Mentor engineers across levels, providing technical leadership on perception systems and ML methodology.

Role Description We're looking for a Machine Learning Engineer (L5) to design and scale the next generation of intelligent systems that power data-driven decision-making across Block—from Cash App and Square to Corporate domains like Treasury, Cost, and Accounting. You'll build models and AI-driven workflows that don't just predict outcomes—they help shape them. Working across the full ML lifecycle, you'll transform raw data into foresight through advanced modeling, agentic AI workflows, and automation frameworks that enable faster, smarter decisions at scale. You'll partner closely with analytics and data science teams to bring experimental models into production and with finance and operations partners to build explainable, self-optimizing systems that make forecasts and insights transparent, actionable, and continuously learning. Qualifications - 5+ years of experience in software or ML engineering, with hands-on experience delivering production-grade ML systems. - Deep understanding of applied ML and forecasting, including time-series, regression, and value prediction modeling. - Strong proficiency in Python and common ML libraries such as scikit-learn, XGBoost, LightGBM, and NumPy/pandas. - Experience building data pipelines using tools such as Airflow, Spark, or similar orchestration systems, and working with BigQuery or other large-scale data warehouses. - Familiarity with model explainability techniques (e.g., SHAP, feature attribution, uncertainty quantification). - Excellent analytical and communication skills; able to connect model design to business objectives. - Proven ability to work cross-functionally and drive high-impact results in fast-paced environments. - Experience in forecasting or planning models in fintech, consumer, or marketplace settings. - Exposure to automated model serving, monitoring, or feedback loops in production. - Background in statistical modeling, uncertainty estimation, or model interpretability research. Requirements - Design and implement forecasting, financial, or optimization models that power strategic decisions across Block. - Build end-to-end ML pipelines for training, deployment, and monitoring, ensuring reproducibility and performance at scale. - Collaborate with Data Science to productionize experimental models and integrate them into live systems. - Partner with Analytics & Finance teams to ensure forecasts are interpretable, accurate, and aligned with business objectives. - Develop or contribute to explainability tools that communicate model drivers, confidence, and uncertainty to stakeholders. - Improve data pipelines and workflows using systems like Airflow, BigQuery, and Spark. - Establish and document best practices for model evaluation, experimentation, and maintenance. - Translate complex technical findings into clear, actionable recommendations for non-technical partners. - Contribute to a culture of curiosity, high-quality engineering, and continuous learning within the AIM organization. Benefits - Remote work - Medical insurance - Flexible time off - Retirement savings plans - Modern family planning

Hey, it's time for you to join us showing the world we are the company that is changing paradigms, where we revolutionize the hours, minutes and seconds! Do you want to know why Rappi? ⭐️ WE SEE OPPORTUNITIES where others see problems ⭐️ WE SEE CLOSE where others see distance ⭐️ WE SEE ADRENALINE where others see pressure. Join a team where we are all capable of EVERYTHING, where we all have the same opportunities, regardless of gender identity, race, religion, nationality, age, disability, training or experience. Did you like what you have read so far? Find out how you will deliver magic together with us through your Rappi mission 🧡 Check out how it will impact our ecosystem: We are seeking a highly skilled and experienced Machine Learning Engineer to join our Merchants and Makers Data Science Models Team. In this critical role, you will be responsible for building and optimizing models that directly impact merchant profitability and Ads performance, such as the Profit Model and Smart Bidding systems. As a key player in the Merchants & Makers Science organization, you will have the opportunity to make a significant impact on our business performance and growth. If you are passionate about delivering world-class ML systems and contributing to a cutting-edge tech startup, then we want to hear from you As part of Rappi, you will be responsible for: - Design, implement, and deploy core machine learning models such as the Profit Model (for optimal promo configuration) and Smart Bidding (for Ads optimization). - Collaborate with a cross-functional team of engineers, data scientists, and product managers to develop, test, and deploy machine learning models for merchant-facing platforms. - Perform feature engineering and selection to improve the overall effectiveness of our merchant data science models. - Work closely with the data infrastructure team to ensure seamless integration of machine learning models with our existing systems and data pipelines. - Continuously monitor and analyze merchant model performance (e.g., ROAS, profit uplift), identifying opportunities for improvement and implementing necessary changes. - Leverage and evaluate AI tools, such as Claude code, to accelerate model development and improve code quality and efficiency. - Mentor junior team members and contribute to the growth of the team's overall expertise in machine learning and merchant science. Good and now, what are the requirements for me to be part of this neon universe? - BSc or MSc in Computer Science, Engineering, or a related field with a focus on machine learning; - PhD is a plus. - 4+ years of experience in machine learning engineering/data scientist, preferably in Merchants Ads optimization (e.g., Smart Bidding, ROAS optimization) or Pricing/Promotions models (e.g., Profit Model) with demonstrable customer and business results. - Strong proficiency in Python, with experience in ML libraries and frameworks such as TensorFlow, PyTorch, or scikit-learn. - Familiarity with data processing and ETL tools such as Airflow, Snowflake, Postgres, Kafka, and Redis. - Proven experience with large-scale, complex systems and the ability to adapt to a fast-paced, rapidly evolving environment. - Excellent problem-solving and analytical skills, with a passion for optimizing algorithms and models for high performance. - Strong communication and collaboration skills, with the ability to work effectively within a diverse, cross-functional team. - Fluency in Spanish (written and spoken) is required; proficiency in English is strongly preferred. - Preference will be given to candidates in Latin America. Globally-located candidates are possible in the right circumstances. Worker type: Regular Company: Rappi Technology Argentina For more information check our website https://about.rappi.com/es and check our reviews on Glassdoor https://acortar.link/Eqm07Q we are waiting for you to build and deliver the magic together! #Rappi 🧡

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. - 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 and/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. Responsible Use of AI in Recruitment At Thoughtworks, we use AI tools to support our recruitment team with administrative tasks such as drafting communications, scheduling interviews and writing job descriptions. Crucially, our AI tools do not screen, assess, rank or make hiring decisions. Every application is reviewed by our team and all selection decisions are made exclusively by our interviewers and hiring managers. We are committed to fairness and responsible AI. We actively manage our AI systems by testing, monitoring for biased outcomes and implementing mitigation measures. We hold our third-party vendors to these same high standards through a rigorous governance process. For additional information, please see our full Thoughtworks AI Policy for Recruitment. EEO Thoughtworks is an equal-opportunity employer. We are committed to providing equal employment opportunities to all qualified applicants and employees without regard to race, color, religion, sex (including pregnancy, childbirth, and related medical conditions), sexual orientation, gender identity or expression, national origin, ancestry, age, disability, genetic information, marital status, military or veteran status, or any other characteristic protected by applicable federal, state, or local law. We prohibit discrimination and harassment of any kind and are dedicated to providing a work environment free from discrimination and harassment. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, stermination, layoff, recall, transfer, leaves of absence, compensation, and training. Thoughtworks is also an affirmative action employer of veterans and individuals with disabilities. For additional information, please see the Thoughtworks, Inc. Equal Employment Opportunity & Affirmative Action Policy Statement. US - Work Authorization Applicants for employment in the US must have work authorization that does not now or in the future require sponsorship of a visa for employment in the United States. Accommodations Thoughtworks is committed to providing reasonable accommodations to qualified applicants with disabilities or sincerely held religious beliefs, practices, or observances, in accordance with applicable law. If you need a reasonable accommodation to complete any part of the application process, participate in interviews, or otherwise engage in the hiring process, you may request an accommodation by completing this form or speaking with your recruiter. Requests may be made at any stage of the application or interview process. Once a request is received, Thoughtworks will engage in an interactive process with the applicant to determine an appropriate accommodation. Applicants are not required to disclose medical diagnoses or detailed personal information in order to request an accommodation. All accommodation requests will be handled in a timely, confidential, and respectful manner, consistent with applicable legal requirements. Requesting an accommodation will not negatively affect your consideration for employment. Company prohibits retaliation against any applicant for requesting an accommodation or participating in the accommodation process. Accommodations made during the recruitment process are not a guarantee of future or continued accommodations once hired. If you are hired by Thoughtworks, and require an accommodation to perform the essential functions of your role, you may be asked to engage in our reasonable accommodation process. Cancellations As a technology consultancy, the projects we undertake are subject to change based on client needs and agreements. While we strive for consistency, please be aware that project scope or availability may shift, or projects may even be cancelled, during the recruitment and selection process, which is often outside of our direct control. Should the project related to this vacancy be significantly altered or cancelled, all impacted candidates will be promptly and duly informed of the change 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 Salary Benefits: https://www.thoughtworks.com/en-us/careers/benefits The annual salary range posted is subject to many factors and may vary depending on experience, geographic location, job responsibilities, performance, skills and/or training. Salary $172,000—$276,000 USD See here our AI policy.