GenAI Platform / LLM Inference Optimization Engineer (Cloud)

Infosys; Charlotte (NC); On-site; USD 90,000 - 120,000; Full time

Benefits offered by this job

Medical/Dental/Vision/Life Insurance

401(k) plan

Paid Time Off

Job summary

Infosys is seeking a Data Science Consultant 2 in Charlotte, North Carolina, to develop innovative analytics solutions and contribute to data-driven decision-making. You will leverage advanced technologies, including AI, to refine algorithms, optimize models, and ensure data readiness for complex use cases.

The ideal candidate has a Bachelor's degree and demonstrated experience with cloud platforms like GCP or Azure, alongside advanced skills in data science tools such as Kubernetes and TensorRT-LLM. This role supports a collaborative environment focused on ongoing professional development and innovative solutions.

Qualifications

• 3+ years of experience in Data Science or related field.
• Strong hands-on experience with cloud technologies (GCP/Azure).
• Proven expertise in machine learning model development.

Responsibilities

• Develop data preparation tasks, identifying patterns or anomalies.
• Design and develop predictive models to address business challenges.
• Collaborate with stakeholders to refine requirements.

Skills

vLLM

TensorRT‑LLM

Triton

SGLang

Kubernetes

GKE

GCP

Azure

Terraform

Education

Bachelor’s degree or foreign equivalent

Tools

Prometheus

Grafana

SageMaker

Job description

Overview

Infosys Data and Analytics (DNA) unit is at the forefront of transforming data into actionable insights, driving business growth and operational efficiency. We specialize in leveraging advanced AI and analytics to create innovative solutions that address complex business challenges. The team pioneers data‑driven decision‑making, enabling organizations to unlock new opportunities and achieve sustainable success. Join a dynamic team that is revolutionizing how businesses harness the power of data and AI. At Infosys DNA, you’ll work with cutting‑edge technologies, collaborate with industry experts, and contribute to transformative projects that shape the future of business. We foster a culture of continuous learning and growth, ensuring team members thrive in a dynamic, supportive environment.

Data Science Consultant 2 – Responsibilities

• Develop data preparation tasks, identifying patterns or anomalies.
• Ensure data readiness for advanced modeling.
• Develop models for complex use cases, refine algorithms to meet business needs, and deploy scalable, production‑ready solutions.
• Conduct testing, optimize algorithms for performance, reliability, and scalability, and guide teammates in best practices.
• Design and develop predictive models and data‑driven analyses to address business challenges.
• Build, evaluate, and deploy models, standardize code, and contribute to knowledge management.
• Leverage tools like SAS and R/Python to create reusable customizations for non‑ML, ML, and deep learning algorithms, enhance analytics including LLMs, and create innovative, cost‑effective solutions.
• Define analytics problems, execute visualization, analysis, and predictive modeling under guidance.
• Proactively maintain models, implement improvements for accuracy and reliability.
• Apply governance controls to mitigate risks and ensure compliance.
• Analyze performance trends, recommend improvements, and document discrepancies for escalation.
• Maintain comprehensive documentation standards and participate in knowledge transfer sessions.
• Participate in discussions with stakeholders to refine requirements, provide insights, and guide implementation of models.
• Apply the predefined quality measurement framework at an individual task level in the project.
• Deploy complex analytics tools or multi‑system integration and validate deployment success.
• Develop scripts or templates for repeated deployment tasks.
• Contribute to analytic solutions, IP asset creation, and training initiatives.
• Contribute to thought leadership such as papers, innovative non‑ML, ML, deep learning or LLM models, and proofs of concepts.
• Deliver analytics training and contribute to content creation.
• Provide input for segment and unit‑level business plans.

Contribution To The Team

• Deliver scalable, high‑quality analytics solutions aligned to business needs.
• Optimise deployment and performance of models.
• Drive innovation through advanced analytics, automation, and thought leadership.
• Enable team growth through knowledge sharing, training, and standardization.
• Support business planning with data‑driven insights.

Required Skills And Experience

• vLLM, TensorRT‑LLM, Triton, SGLang.
• Quantization (FP8/AWQ/GPTQ), tensor parallelism.
• Performance benchmarking & tuning.
• Kubernetes, GKE, KServe / ML serving patterns.
• Helm, Operators.
• GPU orchestration concepts and scheduling patterns.
• GCP and/or Azure (strong hands‑on).
• Terraform.
• Cloud networking, landing zones, governance/org policies.
• HashiCorp Vault (secrets management).

Observability & SRE

• Prometheus/Grafana, logging, tracing.
• SRE/SLO mindset, reliability engineering.

Preferred Skills And Experience

• Experience in Big Data technologies (e.g., BigQuery, Hadoop).
• Expertise in ML model development, data engineering, and software engineering principles.
• Knowledge of MLOps and AI/ML deployment (e.g., SageMaker, Snowflake); familiarity with CI/CD, DevOps, and automation tools in AI/ML contexts.
• Design and implement LLM inference serving stacks using vLLM, TensorRT‑LLM, Triton Inference Server, SGLang.
• Inference optimization techniques: continuous batching, speculative decoding, KV/prefix caching.
• Quantization: FP8 / AWQ / GPTQ and tuning for GPU utilization.
• Build Kubernetes‑based serving platforms: KServe, Kubernetes ML Serving, GKE, OpenShift (OCP) where applicable.
• Enable GenAI platforms and RAG use cases; integrate LLM services with RAG pipelines.
• Provide reusable internal libraries, templates, and developer enablement assets.
• Collaborate with cross‑functional teams and client stakeholders to productionise LLM workloads at scale.

Additional Required Qualifications

• Bachelor’s degree or foreign equivalent from an accredited institution. Three years of progressive experience in the specialty may be considered in lieu of each year of education.
• Position may require relocation and/or travel to work/project location.
• Candidates authorized to work in the United States without employer‑based visa sponsorship are invited to apply. Infosys cannot provide immigration sponsorship for this role now or in the future.

Benefits

• Medical/Dental/Vision/Life Insurance.
• Long‑term/Short‑term Disability.
• Health and Dependent Care Reimbursement Accounts.
• Insurance (Accident, Critical Illness, Hospital Indemnity, Legal).
• 401(k) plan and contributions dependent on salary level.
• Paid holidays and Paid Time Off.

EEO

Infosys provides equal employment opportunities to applicants and employees without regard to race; color; sex; gender identity; sexual orientation; religious practices and observances; national origin; pregnancy, childbirth, or related medical conditions; status as a protected veteran or spouse/family member of a protected veteran; or disability.