Jobs

BPX GenAI Squad Data Scientist requirement

Data Scientist AIML P2P3

Experience 6- 8 Years

Skillset Required

Expert level understanding of Machine LearningDeep Learning concepts techniques algorithms

Hands on working experience on building end to end MLDL solutions

Expert level proficiency in Python programming is a prerequisite

Strong understanding of objectoriented programming and design principles

Experienced with common data science packages in Python like Pandas Numpy Matplotlib and frameworks such as Tensorflow Pytorch

Handson experience in RESTful APIs development with FlaskAPI FastAPI

Excellent understanding of NLP concepts libraries including Word2Vec TFIDF NLTK SpaCy Gensim BERT GloVe etc

Must have experience in development of NLPNLGNLU projects

Deep understanding of Transformer Architectures including BERT GPT DistillBert

Good understanding of Generative AI concepts like Large Language Models Finetuning Evaluating LLMs PEFT RAG Embeddings Vector Databases etc

Experience in frameworks such LangChain LlamaIndex

Experience with Large Language models such as Llama GPT PaLM etc

Experience with Amazon Bedrock Azure OpenAI GCP GenAI Studio

Expertise in training and finetuning LLMs would be preferred

Proficientcy in model development deployment and optimization techniques

Certifications in GenAIAIML preferred

Experienced in deploying AI solutions in cloud environments

Working knowledge in any of the major cloud services AWSAzure

Working knowledge in either of AWS SageMakerAzure Cognitive ServicesGoogle Vertex AI

Certification in any of the Cloud Platforms AWSAzureGCP

Good problemsolving and critical thinking skills

Familiarity with version control systems Git

Knowledge of SQL NoSQL

Key Roles Responsibilities

Create and maintain highquality reusable code components and libraries for future use

Perform rigorous testing and validation to ensure models perform accurately and efficiently in various conditions

About Autonomize AI

Autonomize AI is revolutionizing healthcare by streamlining knowledge workflows with AI. We reduce administrative burdens and elevate outcomes, empowering professionals to focus on what truly matters — improving lives. We're growing fast and looking for bold, driven teammates to join us.

The Opportunity

We're looking for a hands-on ML/LLM Engineer who’s excited to ship real-world applications — not just benchmarks. You’ll help us build and optimize AI-native systems that blend structured and unstructured data to power decisions in high-stakes domains. This is a mid to senior-level role for someone who’s ready to go deep on applied ML problems — from retrieval to routing to generation — and ship solutions that deliver impact.

What you'll do

Own and optimize pipelines that combine classical ML and LLM-based systems (RAG, scoring, summarization, etc.)

Fine-tune and evaluate LLMs using both open-source and proprietary data

Collaborate with product and engineering teams to build real-world applications in healthcare and biopharma

Implement retrieval strategies, prompt chaining, and inference orchestration for production use cases

Monitor and improve model quality, latency, explainability, and safety

Stay ahead of the curve in LLM evaluation, tuning, and agent-based architectures

Qualifications

3–6 years of experience in applied ML, with at least 1–2 years working with LLMs

Strong Python skills and familiarity with ML/LLM frameworks (PyTorch, Transformers, LangChain, LlamaIndex, etc.)

Comfort with embeddings, vector search, retrieval pipelines, and prompt tuning

Bias for experimentation, clarity, and pushing things into production — fast

Understanding of responsible AI practices, model evaluation, and observability

Experience in healthcare, compliance-sens

About the position

Senior AI Engineer – Real Estate Tech We’re building an innovative product in the real estate space and seeking a Senior AI Engineer to join our founding AI team. This role involves turning generative AI concepts into production-ready features and shaping intelligent software experiences.

Responsibilities

AI Agent Development: Build autonomous and conversational AI agents to enhance productivity and automate workflows.AI/ML System Development: Architect scalable AI systems using AWS AI services and open-source frameworks.Full-Stack Integration: Collaborate with Ruby on Rails backend and React frontend teams for AI feature integration.Data Pipeline Management: Design robust pipelines for real estate datasets to support model training and inference.Performance & Monitoring: Optimize deployed models, APIs, and agents for reliability, accuracy, and cost efficiency.Innovation & Research: Apply LLMs, RAG, and agentic AI to solve complex problems.Technical Leadership: Mentor peers, contribute to coding standards, and influence AI strategy.Lifecycle Ownership: Handle AI development from concept to deployment and iteration.Requirements

5+ years in AI, ML, or software engineering with production AI experienceProficient in Python ; experience with PyTorch, TensorFlow, LangChainHands-on cloud deployment ( AWS preferred )Strong understanding of LLMs, Generative AI, RAG, data structures, algorithms, distributed systemsExcellent collaboration and cross-functional teamworkNice-to-haves

Experience with Ruby on Rails and React integrationKnowledge of vector databases (Pinecone, FAISS, Weaviate)Familiarity with MLOps tools (SageMaker, MLflow)Interest in real estate technology

Job Summary

As an LLM Engineer at our forward-thinking education technology company, you will design, develop, and optimize large language model solutions that transform digital learning experiences. The ideal candidate is innovative and technically skilled, with a passion for applying AI to enhance educational content, personalized learning, and academic support tools. You will collaborate with cross-functional teams to deliver scalable, ethical, and high-impact LLM-powered solutions tailored to the needs of students and educators.

Must-Haves:

We are seeking a candidate with proven experience developing and deploying large language models, ideally with applications in education or e-learning. You must be proficient in Python and familiar with leading ML/AI frameworks (such as TensorFlow, PyTorch, or Hugging Face Transformers). A strong understanding of NLP, prompt engineering, and model evaluation is essential. Experience with cloud platforms and a solid grasp of data privacy and ethical AI in education are highly valued. Excellent communication skills and the ability to explain complex technical concepts to non-technical stakeholders are required.

Responsibilities:

Design, develop, and optimize LLM-based applications for educational use cases, such as adaptive tutoring, content generation, and automated assessment.
Fine-tune, evaluate, and maintain LLMs using relevant educational datasets and benchmarks.
Implement prompt engineering and in-context learning strategies to improve model performance and user experience.
Collaborate with educators, product managers, and engineers to align LLM solutions with pedagogical goals and user needs.
Develop and maintain robust, scalable APIs and services for LLM deployment in production environments.
Ensure data privacy, security, and compliance with educational standards and regulations.
Document technical processes, model architectures, and evaluation results for internal and external stakeholders.
Stay curre

Strategic/Functional

Define and drive the organization's AI strategy and roadmap aligned with business goals
Educate leadership and cross-functional teams on AI capabilities, use cases, and best practices
Identify high-impact AI/ML use cases across departments
Provide guidance on responsible AI, governance, and compliance, especially in Public Sector settings
Collaborate with stakeholders to translate business needs into AI-driven solutions
Technical

Design high-level AI/ML architectures and solution frameworks
Evaluate and recommend tools, platforms, and frameworks (e.g., cloud AI services)
Guide teams on data readiness, model lifecycle, and deployment strategies
Ensure scalability, security, and performance of AI solutions
Stay updated with the latest trends in Generative AI, LLMs, and AI platforms


Required Skills & Experience:

8+ years of experience in AI/ML, Data Science, or Solution Architecture
Proven experience as an AI Architect / AI Consultant / ML Architect
Strong understanding of AI/ML frameworks (TensorFlow, PyTorch, Scikit-learn, etc.)
Experience with cloud platforms (AWS, Azure, or GCP AI services)
Ability to communicate complex AI concepts to non-technical stakeholders
Experience in defining AI strategy and roadmaps


Preferred Qualifications:

Experience working with Public Sector / Government clients
Exposure to Generative AI / LLMs (e.g., GPT, RAG architectures)
Knowledge of AI governance, ethics, and compliance frameworks
Prior experience in advisory or consulting roles

Build real AI systems—for real public impact.
Louisville Metro Government is seeking an Applied AI Engineering to serve as a hands-on builder and trusted technical advisor as we scale applied AI across city services.
This role blends modern AI engineering with strategic civic leadership. You will design, prototype, and integrate AI solutions while advising executive leadership on what is possible, what is risky, and what is worth scaling. You will help define Louisville Metro’s emerging AI platform, technical standards, and architectural patterns.
What You’ll Do

Partner with the CAIO, AI Product Lead, and departments to identify high-impact AI use cases.
Design and build AI solutions such as Q&A assistants, document intelligence, routing and triage tools, and workflow automations.
Serve as a technical advisor on AI capabilities, constraints, and risks.
Evaluate and integrate third-party AI platforms, ensuring compliance with security, data, and interoperability standards.
Collaborate with data, security, and infrastructure teams to define reusable technical patterns and reference architectures.
Design and execute experiments, proofs-of-concept, and pilot evaluations.
Communicate complex technical concepts in clear, accessible language to nontechnical stakeholders.
Develop and maintain technical documentation, runbooks, and operational handoffs.

Required Qualifications

Bachelor’s degree in Computer Science, Data Science, Engineering, Information Systems, or a related field.
Three (3) years of professional experience in software engineering, machine learning engineering, data engineering, or applied AI development (or equivalent experience).
Proficiency in Python and experience with modern AI/ML or LLM frameworks (e.g., PyTorch, TensorFlow, LangChain, LlamaIndex).
Experience building applied AI solutions such as chatbots, recommendation systems, document pipelines, and RAG architectures.
Experience with cloud platforms (AWS, Azure, or GCP), containerization, CI/C

• *Title: Application Security (AppSec) + AI Engineering
• *Location: Iselin, NJ (Main) and other Cyber prime locations like Minneapolis, MN, Chander AZ, Dallas, TX (Los Colinas), Charlotte, NC
• *Duration: 6 Months Contract with Possible Ext.
• *Onsite Expectation: 3 days/week (Tuesday–Thursday)
• *JD:
• *Core focus:
• *Application Security (AppSec) + AI Engineering
• *Strong Application Security background

Hands-on with AppSec tools like:
• Checkmarx (critical)
• Other SAST/DAST tools

AI-driven Code Security & Remediation (production-level experience)
• Using AI to:
• Auto-generating secure code fixes
• Detect vulnerabilities
• Generate code remediation suggestions
• Integrating AI into security workflows

Tools / Platforms
• OpenAI (PRIMARY focus)
• GitHub Copilot
• Cloud-based AI coding tools

Real Use Cases Expected
• Deploying AI tools within AppSec pipelines
• Integrating AI with tools like Checkmarx
• Automating vulnerability remediation
• Improving developer productivity using AI

Required Tech Stack
• Python
• Exposure to TensorFlow / PyTorch
• Experience with:
• JIRA (tracking)
• Confluence (documentation)
• True Engineer background required

AppSec Tools and AI tooling
• Focus on AppSec AI eng. Deploying AI toolsto complement existing Appsec tools like Checkmarx and Black Duck
• experience in deploying AI tools for AppSec processes, including auto code remediation.
• The role requires experience with models like Copilot, OpenAI, and Entropic Cloud for code remediation.
• Candidates should have production experience implementing AI tools at scale, not just proof of concept (POC) code.
• The role is specific to AppSec AI engineering, not traditional AI engineering roles.
• role involves writing frameworks against AI models to remediate Checkmarx findings, not directly working with Checkmarx queries.
• various AI models.
• *--------
• *Thanks.
• *Regards,
• *Ashish
• *Email ID: ashish@Hireontech.com**

Databricks is a data and AI company that helps organizations build and productionize AI applications. The AI Forward Deployed Engineering team is seeking an AI Engineer to develop cutting-edge GenAI solutions and serve as a trusted technical advisor to federal government customers.

Responsibilities
• Develop cutting-edge GenAI solutions, incorporating the latest techniques from our Mosaic AI Research to solve customer problems
• Own production rollouts of consumer and internally facing GenAI applications
• Serve as a trusted technical advisor to customers across a variety of domains
• Present at conferences such as Data + AI Summit, recognized as a thought leader internally and externally
• Collaborate cross-functionally with the product and engineering teams to influence priorities and shape the product roadmap

Skills
• U.S. citizenship and eligibility for a U.S. government secret clearance are required to access classified information
• Experience working with U.S. federal civilian, state, or local agencies
• Experience building GenAI applications, including RAG, multi-agent systems, Text2SQL, fine-tuning, etc., with tools such as HuggingFace, LangChain, and DSPy
• Expertise in deploying production-grade GenAI applications, including evaluation and optimizations
• Extensive years of hands-on industry data science experience, leveraging common machine learning and data science tools (i.e., pandas, scikit-learn, PyTorch, etc.)
• Experience building production-grade machine learning deployments on AWS, Azure, or GCP
• Graduate degree in a quantitative discipline (Computer Science, Engineering, Statistics, Operations Research, etc.) or equivalent practical experience
• Experience communicating and/or teaching technical concepts to non-technical and technical audiences alike
• Passion for collaboration, life-long learning, and driving business value through AI
• Experience using the Databricks Intelligence Platform and Apache Spark™ to process large-scale distributed