About Albertsons Companies Inc.:

As a leading food and drug retailer in the United States, Albertsons Companies, Inc. operates over 2,200 stores across 35 states and the District of Columbia. Our well-known banners across the United States, including Albertsons, Safeway, Vons, Jewel-Osco and others, serve more than 36 million U.S customers each week. We build and shape technology solutions that solve customers’ problems every day, making things easier for them when they shop with us online or in a store.

We have made bold, strategic moves to migrate and modernize our core foundational capabilities, positioning ourselves as the first fully cloud-based grocery tech company in the industry.

Our success is built on a one-team approach, driven by the desire to understand and enhance the customer experience. By constantly pushing the boundaries of retail, we are transforming shopping into an experience that is easy, productive, fun and engaging.

About Albertsons Companies

India

At Albertsons Companies India, we're not just pushing the boundaries of technology and retail innovation, we're cultivating a space where ideas flourish and careers thrive. Our workplace in India is a vital extension of the Albertsons Companies Inc. workforce and important to the next phase in the company’s technology journey to support millions of customers’ lives every day.

At the Albertsons Companies India, we are raising the bar to grow across Technology & Engineering, AI, Digital and other company functions, and transform a 165-year-old American retailer.

At Albertsons Companies

India, associates collaborate directly with international teams, enhancing decision-making processes and organizational agility through exciting and pivotal projects. Your work will make history and help millions of lives each day come together around the joys of food and inspire their well-being.

Senior Engineer Machine

Learning

KEY RESPONSIBILITIES

Design, train, evaluate, and deploy ML models for anomaly detection, incident prediction, alert classification, and signal correlation.

Conduct exploratory data analysis, statistical modeling, and data visualization to uncover patterns and inform model development.

Build robust feature engineering, validation,



and inference pipelines that operate at scale.

Architect and maintain model-serving infrastructure, online scoring services, and batch prediction workflows.

Design, execute, and analyze A/B tests and controlled experiments to validate model impact and guide product decisions.

Monitor model drift, latency, throughput, and operational health in production; define SLOs and runbooks.

Own model performance and reliability; lead root cause analysis for model failures and data pipeline incidents.

Build and optimize microservices and APIs for model inference, agent orchestration, and event processing.

Partner with SRE, platform, and data teams to ensure seamless integration, scalability, and cost efficiency.

Drive MLOps best practices: versioning, experiment tracking, automated retraining, and CI/CD for ML.

Apply rigorous experimental design and statistical methods to validate hypotheses and ensure reproducibility.

Mentor junior and mid-level engineers on production ML engineering, system design, data science best practices, and debugging.

Contribute to technical documentation, architectural decision records, and operational playbooks. REQUIRED QUALIFICATIONS:

Bachelor's degree in Computer Science, Engineering, Statistics, Mathematics, or a related quantitative field.

8+ years of experience in machine learning engineering, software engineering, data science, or applied research.

4+ years of hands-on experience building, deploying, and operating ML systems in production.

Expert-level Python and deep familiarity with ML frameworks (PyTorch, TensorFlow, XGBoost).

Strong foundation in statistical analysis, experimental design, and exploratory data analysis.

Strong understanding of MLOps, model monitoring, and distributed systems fundamentals.





Demonstrated ability to derive insights from large-scale datasets and deliver high-impact ML capabilities in cross-functional enterprise teams. MANDATORY SKILLS:

Advanced Python and production ML frameworks (PyTorch, TensorFlow, XGBoost)

End-to-end ML pipeline design: feature engineering, training, validation, inference, and monitoring

Statistical analysis, hypothesis testing, and experimental design

Data exploration, visualization, and communication of insights to diverse stakeholders

A/B testing and causal inference for model and product evaluation

MLOps practices: model versioning, experiment tracking, CI/CD for ML, and automated deployment

Model monitoring, drift detection, latency optimization, and production debugging

Docker, Kubernetes, and cloud-native microservices architecture

REST API design and scalable backend services for real-time and batch inference

Anomaly detection, time-series modeling, and signal classification for observability

Observability platform integration and production incident management for ML systems

System design for high-availability, low-latency, and cost-efficient ML services

SQL and large-scale data manipulation PREFERRED QUALIFICATIONS:

Master's in Computer Science, Statistics, Mathematics, or a related quantitative field.

Experience with LLM-powered applications and agentic frameworks (LangChain, LangGraph).

Familiarity with causal ML and graph-based reasoning for root-cause analysis.

Experience with feature stores, streaming inference, and event-driven ML.

Knowledge of OpenTelemetry, Grafana, Prometheus, and SRE operating models.

Exposure to multi-cloud environments (Azure, AWS, GCP) and hybrid deployments.

Experience with data visualization tools and frameworks.

Published research, patents, or open-source contributions in ML, data science, or systems engineering. KEY SKILLS:

Python, PyTorch, TensorFlow, XGBoost, Pandas, NumPy, SciPy, Scikit-learn

SQL, large-scale data processing, exploratory data analysis

Statistical modeling, hypothesis testing, experimental design, A/B testing

Data visualization (Matplotlib, Seaborn, Plotly) and storytelling with data

MLOps, Docker, Kubernetes, microservices, CI/CD

Model monitoring, drift detection, performance tuning

Observability, SRE collaboration, production ownership

📌 Senior Engineer ML-28191] (Bengaluru)
🏢 Albertsons Companies India
📍 Bengaluru