AI/ML Architect

Job not on LinkedIn

🔥 0 minutes ago

🇮🇳 India – Remote

⏰ Full Time

🟠 Senior

🔴 Lead

🤖 Artificial Intelligence

👻 Ghost score 10%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Alight Solutions

WebsiteLinkedInAll Job Openings

10,000+ employees

🤝 B2B

🏥 Healthcare

☁️ SaaS

💰 $22.5M Post-IPO Secondary - Alight Solutions on 2023-08

B2B • Healthcare • SaaS

Alight Solutions is a leading benefits administration provider that delivers health, wealth, leave, and related HR point solutions for large organizations and their employees. The company helps manage benefits administration and human capital-related processes for enterprises, serving many of the world’s largest organizations and over 30 million people. Alight also emphasizes product and technology roles, corporate sustainability, total rewards, and a focus on transforming lives and organizations by maximizing health, financial and work wellbeing.

📋 Description

• Design, build, and deploy scalable AI/ML solutions as an individual contributor • Write production-grade code and build machine learning models and ML platforms • Develop and deploy AI-powered features and tools that optimize employee experiences and drive business outcomes • Design and develop search and chat applications using Agentic AI • Design and develop AI paved paths for the engineering organization • Design experiments to evaluate machine learning model and application performance • Analyze and interpret experiment results to improve model performance • Evaluate new tools and technologies and assess their potential business impact • Work with stakeholders to develop and tune algorithms for business needs • Explain technical concepts in non-technical terms to educate business partners • Evaluate, fine-tune, and deploy LLMs and foundation models • Implement RAG, guardrails, prompt engineering, and LLM security practices • Write production-quality Python code for feature engineering, model evaluation, and interface services/APIs • Build MCPs, tools, pre-plugin and post-plugin functionality with Spring AI • Build high-performance ingestion pipelines • Work across AWS, data engineering, ML/GenAI, and data ingestion • Work with CI/CD pipelines including GitHub Actions, GitLab, and Jenkins • Mentor engineers on ML best practices without direct people management • Collaborate with cross-functional engineering, product, and domain teams on a global agile team

🎯 Requirements

• 8–10 years of overall experience in Data Engineering, Ingestion, AI/ML, or GenAI-related projects • 5+ years of experience in AI/GenAI/ML projects • Master’s degree with preferred concentrations in Computer Science, Data Science, Math, Actuarial Science, Engineering, or a related field • Strong hands-on coding skills • Experience with Python or Spark, including ScalaSpark or PySpark • Experience with machine learning libraries such as TensorFlow, Keras, and PyTorch • Conversant with Java and Spring AI • Conversant with Spring Boot services • Experience with data preparation and data engineering, including data cleaning, feature engineering, and data transformation • Knowledge of deep learning architectures and techniques, including CNNs, RNNs, and reinforcement learning • Familiarity with AWS data and data science tools, including SageMaker, Glue, and Lambdas • Experience in Agile and DevOps development processes • Ability to clearly communicate complex technical concepts to non-technical audiences • Background check may include government ID validation, education verification, employment verification, criminal check, sanctions/watch-list search, credit check, and/or drug test • Virtual interviews must be conducted on video

🏖️ Benefits

• Health benefits starting Day One • Wellbeing programs • Retirement plans • Career growth opportunities • Continuing education and training • Competitive total rewards package • Potential for occasional travel to physical office locations