Job Summary

CTG Tracking ID:RDTM10
HM Name:52292010 Pignatelli
"Skills & Qualifications
Technical Skills:
- Strong proficiency in Python, SQL, and software engineering best practices (clean code, design patterns, testing, code reviews)
- Enterprise architecture experience for AI/ML platforms (reference architectures, non-functional requirements, capacity planning, HA/DR)
- Advanced ML/GenAI stack: classical ML + deep learning; LLMs, embeddings, RAG, prompt engineering, evaluation frameworks, guardrails/safety patterns
- MLOps/LLMOps: CI/CD for ML, feature stores, experiment tracking, model registry, automated validation, canary/blue-green deployments, monitoring (quality, drift, latency), incident management
- Cloud & platform engineering (AWS/GCP/Azure): IAM, networking basics, containers (Docker), orchestration (Kubernetes), serverless patterns; Infrastructure as Code (Terraform/Bicep/CloudFormation)
- Data engineering foundations: batch/streaming processing, data quality, lineage, governance; familiarity with modern data stacks (e.g., Databricks/Spark, Kafka)
- Security & compliance: secure SDLC, secrets management, encryption, threat modeling, privacy-by-design; understanding of enterprise governance requirements
- Observability & reliability: logging, metrics, tracing, SLO/SLI, performance tuning, cost optimization (FinOps for AI workloads)
- Tooling: Linux, Git, artifact management, CI systems (e.g., GitHub Actions/Azure DevOps/Jenkins)

**Soft Skills:**
- Strong analytical and problem-solving skills
- Ability to work collaboratively in team environments
- Excellent communication skills to convey complex insights clearly"
"Optional (Telco / Networking – 4G/5G):
- Understanding of 4G/LTE and 5G architectures and interfaces (EPC/5GC, RAN concepts, control/user plane separation)
- Familiarity with telecom protocols and networking fundamentals (IP/MPLS, BGP/OSPF basics, QoS, VXLAN), troubleshooting and packet analysis
- Experience with cloud-native telco patterns (CNFs, service mesh, edge/MEC), high-throughput/low-latency design constraints, and resiliency requirements"
"Job Posting: Data Scientist / ML Engineer
At HCLTech, our Communications Technology Group (CTG) is driving the future of innovation through our AI Program. We are modernizing processes, transforming products, and pioneering new AI-driven features to help our clients stay ahead in an increasingly digital world. As part of this program, we are building a talented team of Data Scientists and Machine Learning Engineers who are eager to shape the next generation of AI solutions.
We are looking for passionate and skilled Data Scientists and Machine Learning Engineers to join our dynamic team. If you are driven by curiosity, motivated to create real-world impact, and eager to work with cutting-edge technologies, this opportunity is for you.
Required / Desired Experience
- 8–12+ years of proven experience in AI/ML engineering, data platforms, and enterprise-grade production deployments
- Strong hands-on track record designing and operating scalable ML/GenAI services (APIs, batch/streaming inference), with clear ownership of reliability, security, and cost
- Experience leading technical design reviews, driving architectural decisions, and mentoring engineers in cross-functional teams (product, data, platform, security)
- Demonstrated expertise in production MLOps/LLMOps (CI/CD, automated testing, model/data versioning, monitoring, drift, rollback, governance)
- Comfortable translating business problems into measurable AI outcomes (KPIs), and communicating trade-offs to both technical and non-technical stakeholders
Key Responsibilities
- Analyze and interpret large datasets to deliver 

Key Responsibilities

1. To design and architect large-scale solutions, ensuring scalability, performance, and security.
2. To train and develop team so as to ensure that there is an adequate supply of trained manpower in the said technology and delivery risks are mitigated.
3. To continuously upskill with cutting-edge tech to deliver high-quality, future-proof solutions meeting client expectations and industry standards.
4. To leverage domain/tech expertise to gather client needs, deliver solutions, and craft a technology strategy aligned with business goals.

Skill Requirements

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Other Requirements

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