Machine Learning Engineer

Our most valuable asset is our people .

At ZS we honor the visible and invisible elements of our identities, personal experiences and belief systems the ones that comprise us as individuals, shape who we are and

make us unique. We believe your personal interests, identities, and desire to learn are part of your success here. Learn more about our diversity, equity, and inclusion efforts and the networks ZS supports to assist our ZSers in cultivating community spaces, obtaining the resources they need to thrive, and sharing the messages they are passionate about.

What youll do:

Platform and Tool Development

• Design and build scalable platforms and tools using advanced machine learning techniques, including data parsing, chunking, and information extraction.

• Apply Bayesian programming methods to solve complex problems and enhance system capabilities.

LLM Integration & Optimization

• Implement and productionalize large language models (LLMs) using modern frameworks such as LangChain , optimizing for performance and minimizing issues like hallucinations.

Problem Identification & Solution Architecture

• Partner with stakeholders to identify impactful challenges and architect innovative ML solutions that align with both business priorities and technical feasibility.

Data Analysis & Feature Engineering

• Explore and analyze datasets to identify actionable insights, enabling the development of ML systems and new product features.

• Engineer effective features to maximize model accuracy and applicability in production.

Model Development & Evaluation

• Build, train, and fine-tune machine learning models to meet key performance objectives .

• Evaluate models rigorously using relevant metrics to ensure they are ready for real-world deployment.

Scalable Code & API Development

• Write clean, production-ready code for ML pipelines, ensuring modularity, scalability, and maintainability.

• Collaborate with engineering teams to integrate ML models seamlessly with existing services through robust APIs.

Deployment & Monitoring

• Deploy models in production environments, leveraging best practices for scalability and reliability.

• Implement proactive monitoring systems to detect data drift, model degradation, and other performance issues, ensuring long-term stability.

Stakeholder Communication & Alignment

• Clearly communicate ML insights, limitations, and implications to non-technical stakeholders, fostering alignment with organizational goals.

• Act as a trusted advisor, bridging the gap between technical capabilities and business needs.

What youll bring:

Education

• Bachelor s or Master s degree in Computer Science , Statistics, Data Science, or a related technical field. Advanced degrees are a plus.

Experience

• 6+ years of hands-on experience as a Machine Learning Engineer or Data Scientist, with a proven track record of delivering impactful ML solutions in production environments.

Technical Expertise

• Machine Learning Fundamentals: Strong grasp of ML techniques and frameworks, including training/validation workflows, supervised/unsupervised learning, feature engineering, and optimization strategies.

• Programming & Libraries: Advanced proficiency in Python and hands-on experience with ML and data science libraries (e.g., Pandas, NumPy, scikit-learn, PyTorch , TensorFlow, Transformers, spaCy ).

• Data Management & EDA: Expertise in wrangling, cleaning, and transforming raw data into structured formats optimized for machine learning applications.

• Model Evaluation: Deep understanding of performance metrics (e.g., F1-Score, Precision, Recall) and the ability to contextualize and communicate model results effectively to both technical and non-technical stakeholders.

• Production ML: Demonstrated experience in deploying and productionizing ML models, designing pipelines, and implementing monitoring systems to maintain long-term model performance and stability.

Cloud & Infrastructure

• Familiarity with cloud platforms such as AWS, GCP, or Azure, and experience leveraging these environments for ML workflows.

• Exposure to containerization tools like Docker and orchestration platforms like Kubernetes is a strong plus.

Mindset & Problem-Solving

• A creative and analytical thinker, capable of tackling complex technical challenges with innovative, scalable solutions.

• Passionate about learning and integrating new tools, technologies, and methodologies to stay at the forefront of ML advancements.

Communication & Collaboration

• Strong interpersonal skills with the ability to distill technical complexity into accessible insights for diverse audiences.

• A collaborative mindset, with experience working cross-functionally with engineering, product, and business teams.

Perks & Benefits:

ZS offers a comprehensive total rewards package including health and well-being, financial planning, annual leave, personal growth and professional development. Our robust skills development programs, multiple career progression options and internal mobility paths and collaborative culture empowers you to thrive as an individual and global team member.

We are committed to giving our employees a flexible and connected way of working. A flexible and connected ZS allows us to combine work from home and on-site presence at clients/ZS offices for the majority of our week. The magic of ZS culture and innovation thrives in both planned and spontaneous face-to-face connections.

Travel:

Travel is a requirement at ZS for client facing ZSers; business needs of your project and client are the priority. While some projects may be local, all client-facing ZSers should be prepared to travel as needed. Travel provides opportunities to strengthen client relationships, gain diverse experiences, and enhance professional growth by working in different environments and cultures.

Considering applying?

At ZS, were building a diverse and inclusive company where people bring their passions to inspire life-changing impact and deliver better outcomes for all. We are most interested in finding the best candidate for the job and recognize the value that candidates with all backgrounds, including non-traditional ones, bring. If you are interested in joining us, we encourage you to apply even if you dont meet 100% of the requirements listed above.

ZS is an equal opportunity employer and is committed to providing equal employment and advancement opportunities without regard to any class protected by applicable law.

To Complete Your Application:

Candidates must possess or be able to obtain work authorization for their intended country of employment.An on-line application, including a full set of transcripts (official or unofficial), is required to be considered.