Engineer 2 - Machine Learning
Chennai, India
Overview
Make your mark at Comcast -- a Fortune 30 global media and technology company. Become part of our award-winning, international engineering team that turns big ideas into cutting-edge products, platforms, and solutions that our customers love. We create space to innovate, and we recognize, reward, and invest in your ideas, while ensuring you can proudly bring your authentic self to the workplace. You’ll do the best work of your career right here.
Success Profile
What makes a successful Engineer 2 - Machine Learning at Comcast? Check out these top traits and explore role-specific skills in the job description below.
- Results-driven
- Adaptable
- Inventive
- Entrepreneurial
- Team Player
- Problem-Solver
Responsibilities
Engineer 2 - Machine Learning
Job Summary
Responsible for contributing to the development and deployment of machine learning algorithms. Evaluates accuracy and functionality of machine learning algorithms as a part of a larger team. Contributes to translating application requirements into machine learning problem statements. Analyzes and evaluates solutions both internally generated as well as third party supplied. Contributes to developing ways to use machine learning to solve problems and discover new products, working on a portion of the problem and collaborating with more senior researchers as needed. Works with moderate guidance in own area of knowledge.Job Description
•Business Segment: Direct-to-Consumer (DTC)
Company Description:
Our Direct-to-Consumer (DTC) portfolio is a powerhouse collection of consumer-first brands, supported
by media industry leaders, Comcast, NBCUniversal, and Sky. When you join our team, you’ll work across
our dynamic portfolio including Peacock, NOW, Fandango, SkyShowtime, Showmax, and TV Everywhere,
powering streaming across more than 70 countries globally.
And evolution doesn’t stop there. With an unequaled scale, our teams make the most out of every
opportunity to collaborate and learn from one another. We’re always looking for ways to innovate
faster, accelerate our growth, and consistently offer the verybest in the consumer experience. But most
of all, we’re backed by a culture of respect. We embrace authenticity and inspire people to thrive.
About the Role:
We are seeking an experienced Data Scientist to join our growing Operational Intelligence team. You will
play a key role in building intelligent systems that help reduce alert noise, detect anomalies, correlate
events, and proactively surface operational insights across our large-scale streaming infrastructure.
You’ll work at the intersection of machine learning, observability, and IT operations, collaborating
closely withPlatformEngineers, SREs,IncidentManagers,OperatorsandDevelopers tointegrate smart
detection and decision logic directly into our operational workflows.
This role offers a unique opportunity to push the boundaries of AI/ML in large-scale operations. We
welcome curious minds who want to stay ahead of the curve, bring innovative ideas to life, and improve
the reliability of streaming infrastructure that powers millions of users globally.
What You’ll Do:
•Design and tune machine learning models for event correlation, anomaly detection, alert
scoring, and root causeinference
•Engineer features to enrich alerts using service relationships, business context, change history,
and topological data
•Apply NLP and ML techniques to classify and structure logs and unstructured alert messages
•Develop and maintain real-time and batch data pipelines to process alerts, metrics, traces, and
logs
•Use Python, SQL, and time-series query languages (e.g., PromQL) to manipulate and analyze
operational data
•Collaborate with engineering teams to deploy models via API integrations, automate workflows,
and ensure production readiness
•Contribute to the development of self-healing automation, diagnostics, and ML-powered
decision triggers
•Design and validate entropy-based prioritization models to reduce alert fatigue and elevate
critical signals
•Conduct A/B testing, offline validation, and live performance monitoring of ML models
•Build and share clear dashboards, visualizations, and reporting views to support SREs, engineers,
and leadership
•Participate in incident postmortems, providing ML-driven insights and recommendations for
platform improvements
•Collaborate on the design of hybrid ML + rule-based systems to support dynamic correlation and
intelligent alert grouping
•Lead and support innovation efforts including POCs, POVs, and exploration of emerging AI/ML
tools and strategies
•Demonstrate a proactive, solution-oriented mindset with the ability to navigate ambiguity and
learn quickly
•Participate in on-call rotations and provide operational support as needed
Qualifications:
•Bachelor's or Master's degree in Computer Science, Data Science, Machine Learning, Statistics or
a related field
•3+ years of experience building and deploying ML solutions in production environments
•2+ years working with AIOps, observability, orreal-time operations data
•Strong coding skills in Python (including pandas, NumPy, Scikit-learn, PyTorch, or TensorFlow)
•Experience working with SQL, time-series query languages (e.g., PromQL), and data
transformation in pandas or Spark
•Familiarity with LLMs, prompt engineering fundamentals, or embedding-based retrieval (e.g.,
sentence-transformers, vector DBs)
•Strong grasp of modern ML techniques including gradient boosting (XGBoost/LightGBM),
autoencoders, clustering (e.g., HDBSCAN), and anomaly detection
•Experience managing structured + unstructured data, and building features from logs, alerts,
metrics, and traces
•Familiarity with real-time event processing using tools like Kafka, Kinesis, or Flink
•Strong understanding of model evaluation techniques including precision/recall trade-offs, ROC,
AUC, calibration
•Comfortable working with relational (PostgreSQL), NoSQL (MongoDB), and time-series
(InfluxDB, Prometheus) databases
•Ability to collaborate effectively with SREs, platform teams, and participate in Agile/DevOps
workflows
•Clear written and verbal communication skills to present findings to technical and non-technical
stakeholders
•Comfortable working across Git, Confluence, JIRA, & collaborative agile environments
Nice to Have:
•Experiencebuilding or contributing to the AIOps platform(e.g., Moogsoft, BigPanda,Datadog,
Aisera, Dynatrace, BMC etc.)
•Experience working in streaming media, OTT platforms, or large-scale consumer services
•Exposure to Infrastructure as Code (Terraform, Pulumi) and modern cloud-native tooling
•Working experience with Conviva, Touchstream, Harmonic, New Relic, Prometheus, & event-
based alerting tools
•Hands-on experience with LLMs in operational contexts (e.g., classification of alert text, log
summarization, retrieval-augmented generation)
•Familiarity with vector databases (e.g., FAISS, Pinecone, Weaviate) and embeddings-based
search for observability data
•Experience using MLflow, SageMaker, or Airflow for ML workflow orchestration
•Knowledge of LangChain, Haystack, RAG pipelines, or prompt templating libraries
•Exposure to MLOps practices (e.g., model monitoring, drift detection, explainability tools like
SHAP or LIME)
•Experience with containerized model deployment using Docker or Kubernetes
•Use of JAX, Hugging Face Transformers, or LLaMA/Claude/Command-R models in
experimentation
•Experience designing APIs in Python or Go to expose models as services
•Cloud proficiency in AWS/GCP, especially for distributed training, storage, or batch inferencing
•Contributions to open-source ML or DevOps communities, or participation in AIOps
research/benchmarking efforts
•Certifications in cloud architecture, ML engineering, or data science specializations
Comcast is an equal opportunity workplace. We will consider all qualified applicants for employment without regard to race, color, religion, age, sex, sexual orientation, gender identity, national origin, disability, veteran status, genetic information, or any other basis protected by applicable law.
Base pay is one part of the Total Rewards that Comcast provides to compensate and recognize employees for their work. Most sales positions are eligible for a Commission under the terms of an applicable plan, while most non-sales positions are eligible for a Bonus. Additionally, Comcast provides best-in-class Benefits to eligible employees. We believe that benefits should connect you to the support you need when it matters most, and should help you care for those who matter most. That’s why we provide an array of options, expert guidance and always-on tools, that are personalized to meet the needs of your reality – to help support you physically, financially and emotionally through the big milestones and in your everyday life. Please visit the compensation and benefits summary on our careers site for more details.
Education
Bachelor's Degree
While possessing the stated degree is preferred, Comcast also may consider applicants who hold some combination of coursework and experience, or who have extensive related professional experience.
Relevant Work Experience
2-5 Years
Hear from our people
Culture
At Comcast you can have work/life balance in an inclusive environment where you can be your authentic self.
Comcast provides many opportunities to build skills and grow in your career and a top-notch benefits, time off and perks package.
We are committed to delivering reliable, effortless experiences to our customers no matter how they choose to interact with us.
You will build personal relationships on a growing team that while making Xfinity a best-in-class, most-loved brand.

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