Quantiphi

Quantiphi

Associate Technical Architect - ML

USA - Remote · Senior · Full-time

Sponsorship not specifiedDetected 4 days ago
AlgorithmsElasticsearchSnowflakeAWSGCPMachine LearningDeep LearningAirflowNLPLLMsRAGAgentic AIMLOpsAI OrchestrationExcelResearch

Stay score

odds of building a lasting career here

40Risky
Cap-exempt (no lottery)0
Sponsors this role90
Entry-level history0
PERM / green-card track0
Lottery odds40
Fits your clock70

Thin sponsorship signal and lottery-bound. A low-probability bet with your clock running. Prioritize cap-exempt roles and proven entry-level sponsors first.

Lottery odds assume a STEM candidate.

Personalize to your clock →

Employer immigration record

from this employer's Department of Labor filings

Files H-1B transfers

6 transfer filings in the last year, covering 6 workers. Median labor-condition decision: 7 days. An employer that already files transfers is one that can take over an existing H-1B.

Sourced from Department of Labor LCA, PERM and prevailing-wage disclosure data. Employer matching is by name, so figures may be split across an employer's legal entities. Absence of a filing means none appears in our copy of the data, not that none exists.

Community outcomes

No reports yet — be the first to help the next applicant.

About the role

  • While technology is the heart of our business, a global and diverse culture is the heart of our success.
  • We love our people and we take pride in catering them to a culture built on transparency, diversity, integrity, learning and growth.
  • If working in an environment that encourages you to innovate and excel, not just in professional but personal life, interests you- you would enjoy your career with Quantiphi!

Responsibilities

  • 8+ years of relevant hands-on technical experience implementing, and developing cloud ML solutions on AWS.
  • Good Experience developing applications using LLMs with Langchain.
  • Prompt Engineering: Engineer prompts and optimize few-shot techniques to enhance LLM's performance on specific tasks, e.g. personalized recommendations.
  • Response Quality: Collaborate with ML and Integration engineers to leverage LLM's pre-trained potential, delivering contextually appropriate responses in a user-friendly web app.
  • Implement and manage MLOps principles and best practices for Gen AI models
  • Ability to create end to end solution architecture for model training, deployment and retraining using native AWS services such as Sagemaker, Lambda functions, etc.
  • Ability to collaborate with cross-functional teams such as Developers, QA, Project Managers, and other stakeholders to understand their requirements and implement solutions.
  • Lead and collaborate with a high-energy team of talented, driven individuals solving complex, meaningful challenges.
  • 21 Google Cloud Partner of the Year awards in the past 10 years
  • 3 AWS AI/ML Partner of the Year awards

Requirements

  • Proven experience using AWS Sagemaker leveraging different types of data sources, Training jobs, real-time and batch Inference, and Processing Jobs.
  • Must have experience using GenAI frameworks such as vertexAI, OpenAI, AWS Bedrock.
  • Must have Hands-on experience fine-tuning large language models( LLM) and Generative AI (GAI), specifically LLama2.
  • Must have Hands-on experience working with (Retrieval Augmented Generation) RAG architecture and experience using vector indexing such as Opensearch, Elasticsearch.
  • Able to effectively design software architecture as required

Benefits

  • As an Architect, Machine Learning Engineer at Quantiphi, you will be responsible for designing and developing advanced machine learning models and algorithms to solve complex business problems.
  • Hands-on experience on AWS Machine Learning services.
  • Should have experience with Deep Learning Concepts.

Company info

  • We are also proud to be certified as a Great Place to Work-reflecting our commitment to our people and our culture.

This listing is sourced directly from Quantiphi's careers page and normalized into a canonical job model.