Senior Machine Learning Engineer

Responsibilities

• Client Delivery
• Own and drive end-to-end design, implementation, and production deployment of machine learning solutions for enterprise data and AI initiatives.
• Translate business requirements into technical and data engineering solutions that align with phData methodologies, standards, and best practices.
• Ensure engagements are delivered on time, within scope, and with measurable business value for clients.
• Design and create environments and tooling that enable data scientists to build, train, and evaluate models efficiently and securely.
• Work within customer systems to extract, integrate, and prepare data for analytics and model development, ensuring quality, performance, and reliability.
• Define and implement deployment approaches and infrastructure for machine learning models so they can be consumed and maintained by the business.
• Develop and execute operational testing strategies, including QA validation, performance testing, and production rollout plans for models and supporting services.
• Ensure the quality, stability, and observability of delivered solutions through logging, monitoring, testing, and documentation.
• Collaboration & Leadership
• Collaborate with cross-functional partners including data science, data engineering, platform/DevOps, and business stakeholders to deliver successful client engagements.
• Provide technical leadership during discovery sessions, architecture and design reviews, and implementation phases to align on scalable MLOps patterns.
• Ensure high quality in deliverables through code reviews, technical documentation, automated testing, and adherence to security and governance standards.
• Partner with practice and account leaders to identify opportunities to expand engagements, improve delivery patterns, and standardize machine learning deployment approaches.
• Work closely with data scientists to shape model integration patterns, data contracts, and performance requirements that enable deployment at scale in harmony with existing systems and pipelines.
• Practice & Firm Contribution
• Contribute to internal initiatives such as IP development, MLOps accelerators, infrastructure templates, playbooks, and training for colleagues on best practices for deploying ML in production.
• Represent phData with professionalism in all interactions, communicating clearly with both technical and non-technical stakeholders.
• About You
• Required Qualifications

Requirements

• 4+ years of experience in machine learning engineering, software engineering, or data engineering roles building and deploying ML solutions to production.
• Technical / Functional Skills
• Proficiency in modern programming languages such as Python, Scala, Java, or similar.
• Experience building and operating robust data pipelines and distributed data processing solutions using technologies such as Spark, Pandas

Benefits

Additional Information

Join phData , a dynamic and innovative leader in the modern data stack. We partner with major cloud data platforms like Snowflake, AWS, Azure, GCP, Fivetran, Pinecone, Glean, and dbt to deliver cutting-edge services and solutions. We're committed to helping global enterprises overcome their toughest data challenges. phData is a remote-first global company with employees based in the United States, Latin America, and India. We celebrate the culture of each of our team members and foster a community of technological curiosity, ownership, and trust. Even though we're growing extremely fast, we maintain a casual, exciting work environment. We hire top performers and allow you the autonomy to deliver results. 6x Snowflake Partner of the Year (2020, 2021, 2022, 2023, 2024, 2025) Fivetran , dbt , Atlation, and AWS Partner of the Year #1 Partner in Snowflake Advanced Certifications 600+ Expert Cloud Certifications (Sigma, AWS, Azure, Dataiku, etc) Recognized as an award-winning workplace in the US , India , and LATAM Role Overview We are looking for a Senior Machine Learning Engineer to join our Machine Learning team. In this role, you will design, build, and operationalize production-grade machine learning solutions that turn data science models into reliable, scalable business capabilities. You will collaborate closely with clients, data scientists, data engineers, and platform teams to ensure models are deployable, maintainable, and aligned with customer environments. You will focus on robust infrastructure, deployment, and data integration to ensure our solutions deliver measurable impact in production.

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