Lead Engineer (with AI/ML) at Vowels of the People Association · Pune · 4 - 10 years · ₹12L - ₹14L / yr · Raised funding · Posted 16 Jul 2026

About the Role :
As the Lead AI/ML Engineer, you will be responsible for leading the design, development, deployment, and continuous improvement of AI-powered solutions that create measurable impact in education. This role combines hands-on technical execution with engineering leadership, requiring you to architect scalable AI systems, mentor engineers, establish best practices, and collaborate closely with cross-functional teams to deliver production-grade solutions.
You will take ownership of the complete AI development lifecycle—from problem definition and data pipeline design to model training, deployment, monitoring, and optimization—while ensuring high standards of reliability, scalability, security, and performance. The role also involves evaluating emerging AI technologies and driving their adoption to enhance product capabilities and user experience.
Roles and Responsibilities:
- Lead the design, development, and deployment of AI-powered products for production environments.
- Drive technical architecture and decision-making across machine learning models, inference systems, cloud infrastructure, and distributed computing.
- Develop and maintain end-to-end machine learning pipelines, including data ingestion, model training, evaluation, deployment, monitoring, and continuous optimization.
- Design scalable, secure, and high-performance AI services capable of handling production-scale workloads.
- Provide technical leadership by mentoring engineers, conducting code and design reviews, and fostering engineering excellence.
- Establish and promote best practices for software quality, testing, performance optimization, observability, reliability, and maintainability.
- Collaborate closely with Product, Backend, Mobile, and Data teams to deliver robust, scalable, and business-focused AI solutions.
- Research, evaluate, and implement emerging AI technologies to enhance product capabilities and drive innovation.
Required Skills & Qualifications
- Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related technical discipline.
- Minimum 4 years of hands-on experience developing, deploying, and maintaining production-grade AI/ML systems.
- Strong proficiency in Python with excellent software engineering, object-oriented programming, and system design skills.
- Extensive experience with modern machine learning frameworks such as PyTorch, Hugging Face, TensorFlow, or equivalent.
- Proven expertise in deploying, optimizing, and scaling large language models (LLMs) and other AI models for production inference.
- Strong understanding of containerization and cloud-native technologies, including Docker, Kubernetes, AWS, and distributed system architectures.
- Demonstrated ability to lead technical initiatives, mentor engineering teams, and make sound architectural decisions.
- Excellent analytical, debugging, communication, and problem-solving skills.
Preferred Qualifications
- Hands-on experience with Large Language Models (LLMs), Computer Vision, Speech Recognition, Generative AI, or Multimodal AI systems.
- Experience with model optimization and inference technologies such as Quantization, Distributed Training, vLLM, TensorRT, ONNX Runtime, or similar frameworks.
- Prior experience developing AI solutions for the education, public sector, or other large-scale social impact initiatives.
Details:
- Location: Kothrud, Pune.
- Interested candidates should fill in the application on career website https://careers.vopa.in/
- Salary :- 12 LPA to 14 LPA (Depending on last drawn salary, Interview and Skills)

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Kody Technolab Limited is seeking an experienced AI/ML Engineer to design, develop, and deploy cutting-edge Artificial Intelligence and Machine Learning solutions. The ideal candidate will have
strong expertise in Machine Learning, Deep Learning, Generative AI, LLMs, MLOps, and cloud-based AI deployments.
Key Responsibilities
• Design, develop, and deploy Machine Learning and Deep Learning models for classification, regression, recommendation systems, NLP, Computer Vision, and Generative AI applications.
• Build and maintain end-to-end ML pipelines including data preprocessing, feature engineering, model training, validation, evaluation, and deployment.
• Develop AI solutions using PyTorch, TensorFlow, Scikit-learn, Hugging Face, and related frameworks.
• Work with Large Language Models (LLMs) and foundation models such as GPT, BERT, Llama, Claude, and Stable Diffusion.
• Collaborate with product, engineering, and business teams to translate requirements into scalable AI solutions.
• Optimize model performance, scalability, and reliability for production environments.
• Implement MLOps best practices using tools such as MLflow, Docker, Kubernetes, and Kubeflow.
• Stay updated with emerging trends and research in AI, ML, Deep Learning, and Generative AI.
Required Qualifications
• Bachelor’s or Master’s degree in Computer Science, Data Science, Artificial Intelligence, Mathematics, or a related field.
• 7+ years of hands-on experience in AI/ML product development.
• Strong proficiency in Python and ML frameworks including Scikit-learn, TensorFlow, PyTorch, and Hugging Face.
• Experience with Generative AI, LLMs, GANs, VAEs, diffusion models, and prompt engineering.
• Strong understanding of the ML lifecycle including model training, tuning, deployment, monitoring, and optimization.
• Experience with MLOps tools such as MLflow, Docker, Kubeflow, and CI/CD pipelines.
• Experience with AWS, Azure, or GCP cloud platforms.
• Strong problem-solving and analytical skills.
Preferred Skills
• Fine-tuning and deployment of Large Language Models.
• Experience with RAG (Retrieval Augmented Generation) architectures.
• Contributions to open-source AI projects or research publications.
• Knowledge of model interpretability, data annotation, and feature engineering.
• C++ experience for high-performance AI applications.
Why Join Kody Technolab Limited?
Opportunity to work on innovative AI products, Generative AI solutions, robotics integrations,
and enterprise-scale applications while collaborating with a highly skilled technology team.
Visit the Website to know more about us.
Company Website - Kody Technolab | Deep Tech Company in Robotics & AI Solution
Kody Robots | Robotics Company in India for Autonomous Robots
About NonStop io Technologies
NonStop io Technologies is a value-driven company with a strong focus on process-oriented software engineering. We specialize in Product Development and have a decade's worth of experience in building web and mobile applications across various domains. NonStop io Technologies follows core principles that guide its operations and believes in staying invested in a product's vision for the long term. We are a small but proud group of individuals who believe in the 'givers gain' philosophy and strive to provide value in order to seek value. We are committed to and specialize in building cutting-edge technology products and serving as trusted technology partners for startups and enterprises. We pride ourselves on fostering innovation, learning, and community engagement. Join us to work on impactful projects in a collaborative and vibrant environment.
Brief Description:
We're seeking an AI/ML Engineer to join our team. As AI/ML Engineer, you will be responsible for designing, developing, and implementing artificial intelligence (AI) and machine learning (ML) solutions to solve real-world business problems. You will work closely with engineering teams, including software engineers, domain experts, and product managers, to deploy and integrate Applied AI/ML solutions into the products that are being built at NonStop io. Your role will involve researching cutting-edge algorithms and data processing techniques, and implementing scalable solutions to drive innovation and improve the overall user experience.
Responsibilities
● Applied AI/ML engineering; Building engineering solutions on top of the AI/ML tooling available in the industry today. Eg: Engineering APIs around OpenAI
● AI/ML Model Development: Design, develop, and implement machine learning models and algorithms that address specific business challenges, such as natural language processing, computer vision, recommendation systems, anomaly detection, etc.
● Data Preprocessing and Feature Engineering: Cleanse, preprocess, and transform raw data into suitable formats for training and testing AI/ML models. Perform feature engineering to extract relevant features from the data
● Model Training and Evaluation: Train and validate AI/ML models using diverse datasets to achieve optimal performance. Employ appropriate evaluation metrics to assess model accuracy, precision, recall, and other relevant metrics
● Data Visualization: Create clear and insightful data visualizations to aid in understanding data patterns, model behaviour, and performance metrics
● Deployment and Integration: Collaborate with software engineers and DevOps teams to deploy AI/ML models into production environments and integrate them into various applications and systems
● Data Security and Privacy: Ensure compliance with data privacy regulations and implement security measures to protect sensitive information used in AI/ML processes
● Continuous Learning: Stay updated with the latest advancements in AI/ML research, tools, and technologies, and apply them to improve existing models and develop novel solutions
● Documentation: Maintain detailed documentation of the AI/ML development process, including code, models, algorithms, and methodologies for easy understanding and future reference.
Qualifications & Skills
● Bachelor's, Master's, or PhD in Computer Science, Data Science, Machine Learning, or a related field. Advanced degrees or certifications in AI/ML are a plus
● Proven experience as an AI/ML Engineer, Data Scientist, or related role, ideally with a strong portfolio of AI/ML projects
● Proficiency in programming languages commonly used for AI/ML. Preferably Python
● Familiarity with popular AI/ML libraries and frameworks, such as TensorFlow, PyTorch, scikit-learn, etc.
● Familiarity with popular AI/ML Models such as GPT3, GPT4, Llama2, BERT etc.
● Strong understanding of machine learning algorithms, statistics, and data structures
● Experience with data preprocessing, data wrangling, and feature engineering
● Knowledge of deep learning architectures, neural networks, and transfer learning
● Familiarity with cloud platforms and services (e.g., AWS, Azure, Google Cloud) for scalable AI/ML deployment
● Solid understanding of software engineering principles and best practices for writing maintainable and scalable code
● Excellent analytical and problem-solving skills, with the ability to think critically and propose innovative solutions
● Effective communication skills to collaborate with cross-functional teams and present complex technical concepts to non-technical stakeholders
Experience - 4 to 6 year
Location – Ahmedabad/Pune/Indore
- Additional Job Description
Additional Job Description
Required Skills and Experience:
- Strong proficiency in Python and experience with ML/AI libraries (scikit-learn, TensorFlow, PyTorch, Hugging Face ecosystem).
- Hands-on experience with LLMs, RAG, vector databases, and retrieval pipelines.
- Practical experience deploying agentic workflows and building multi-step, tool-enabled agents.
- Experience using Garak (or similar LLM red-teaming/vulnerability scanners) to identify model weaknesses and harden deployments.
- Demonstrated experience implementing content filtering / moderation systems.
- Solid skills working with structured and unstructured data and advanced feature engineering.
- Familiarity with cloud GenAI platforms and services (Azure AI Services preferred; AWS/GCP acceptable).
- Experience building APIs/microservices; containerization (Docker), orchestration (Kubernetes).
- Strong understanding of model evaluation, performance profiling, inference cost optimization, and observability.
- Good knowledge of security, data governance, and privacy best practices for AI systems.
Job Title: Senior AI/ML Engineer
Company: Timble Technologies Pvt. Ltd
Location: Gurugram (Hybrid)
Experience: 2 TO 5 Years
About Us
Timble Glance is a high-growth AI RegTech and B2B SaaS company catering to top-tier BFSI and enterprise clients. We build cutting-edge systems powering 30+ high-scale APIs for digital identity verification, fraud detection, document intelligence, and compliance automation.
Role Overview
We are looking for a hands-on Senior AI/ML Engineer to design, develop, and productionize high-throughput AI/ML and Generative AI systems. You will own the full lifecycle—from problem formulation and data pipelines to deep learning architectures, RAG systems, LLMOps, and model governance—delivering sub-second latency and high reliability across our enterprise products.
Key Responsibilities
· Model Architecture & Deployment: Design, train, and deploy production-scale ML/Deep Learning and GenAI systems (computer vision, document intelligence, OCR, NLP, fraud risk classification, and LLM applications).
· GenAI & LLM Solutions: Develop robust LLM workflows including prompt engineering, fine-tuning, RAG pipelines, semantic search, vector indexing (Pinecone/Milvus/Chroma), and safety guardrails.
· Pipelines & Engineering: Build performant feature extraction and data pipelines; write modular, vectorized, production-grade Python (NumPy, Pandas) and advanced SQL.
· MLOps & Monitoring: Establish end-to-end MLOps/LLMOps standards—model registries, CI/CD, experiment tracking, drift detection, A/B testing, latency optimization, and cost governance.
· Responsible AI & Security: Ensure model decisions comply with enterprise data security, privacy standards, and auditability required by the BFSI sector.
· Collaboration & Ownership: Translate complex business requirements into technical roadmaps, conduct rigorous code reviews, and mentor junior engineers.
Required Qualifications & Skills
· Education: B.Tech / M.Tech in Computer Science, AI/ML, Mathematics, or a related field—Tier-1 institutes (IIT, IIIT, NIT) strongly preferred.
· Experience: 2+ years of hands-on experience developing, deploying, and maintaining ML/Deep Learning or GenAI models in production environments.
· GenAI & NLP Stack: Hands-on experience with LLMs, embeddings, RAG architectures, and frameworks such as LangChain, LlamaIndex, or Hugging Face.
· Deep Learning Frameworks: Strong proficiency in PyTorch or TensorFlow, with deep knowledge of transformer architectures and modern NLP/CV models.
· Software & Data Engineering: Expert-level Python skills (pytest, Git, OOP, asynchronous programming), solid SQL proficiency, and familiarity with data workflows.
· Deployment & Cloud: Practical exposure to cloud platforms (AWS/GCP), containerization (Docker), API frameworks (FastAPI/Flask), and basic orchestration (Kubernetes).
Preferred Qualifications
· Prior domain experience in Fintech, RegTech, Identity Verification (KYC/AML), Fraud Intelligence, or B2B SaaS.
· Experience optimizing models for low latency and inference cost (e.g., ONNX, TensorRT, model quantization).
· Familiarity with workflow orchestrators such as Airflow, Prefect, or Kubeflow.
Job Summary/ Job Opportunity:
This is an excellent opportunity for an ideal candidate with a high level of technical proficiency and meeting the below mentioned criteria -- • Strong experience in Machine Learning, Deep Learning, Generative AI, and Large Language Models (LLMs). • Hands-on experience building and deploying production-grade solutions using Azure OpenAI, OpenAI, LangChain, LangGraph, Semantic Kernel, LlamaIndex, and Agentic AI frameworks. • Strong expertise in Python, API development, microservices, and cloud-native architectures. • Experience designing and implementing RAG solutions, vector databases, embeddings, knowledge retrieval systems, and AI copilots. • Experience with Azure cloud services, MLOps, CI/CD pipelines, monitoring, and model lifecycle management. • Strong understanding of AI governance, responsible AI, security, compliance, and model evaluation frameworks. • Ability to lead technical discussions, provide architectural recommendations, mentor team members, and interact with business stakeholde
Key Objectives and Major Responsibilities:
• Design, develop, and implement scalable AI/ML and Generative AI solutions for enterprise applications. • Lead development of intelligent applications leveraging LLMs, RAG pipelines, AI agents, and document intelligence solutions. • Collaborate with business stakeholders, architects, and product teams to translate business requirements into technical solutions. • Design and optimize data pipelines, vector search solutions, embeddings, and retrieval mechanisms. • Build and maintain REST APIs, microservices, and cloud-native AI applications. • Ensure best practices in coding standards, performance optimization, security, scalability, and maintainability. • Drive AI solution deployment using MLOps practices, CI/CD pipelines, monitoring, and observability frameworks. • Perform code reviews, mentor junior developers, and contribute to capability building within the team
Key Capabilities and Competencies:
Knowledge, Skills, Qualification and Experience
• Degree in B.Tech/M.Tech (Computer Science/IT/Data Science) or related discipline preferred, with 3–4 years of relevant experience in AI/ML, GenAI and total 5-7 years of experience. • Proficiency in Python and hands-on experience with ML libraries (scikit-learn, TensorFlow, PyTorch) and GenAI frameworks/tools. • Strong understanding of machine learning, deep learning, LLMs, prompt engineering, and techniques like RAG and fine-tuning. • Experience with data processing, embeddings, vector databases, APIs, and building scalable AI driven applications. • Good communication skills, ability to work on multiple projects, and eagerness to learn and adapt to evolving AI technologies.
Job Description – AI Engineer (End-to-End Development & Deployment)
Role Summary
We are looking for an AI Engineer with hands-on experience in designing, developing, deploying, and maintaining Generative/Agentic AI solutions in production. The ideal candidate should have end-to-end ownership of AI applications, from development to deployment, monitoring, and optimization.
Key Responsibilities
● Design, build, and deploy Generative/Agentic AI solutions.
● Develop applications using LLMs, RAG, AI agents, and vector databases.
● Build scalable APIs and integrate AI solutions with enterprise applications.
● Implement CI/CD pipelines, containerization, and MLOps best practices.
● Monitor, optimize, and maintain production AI systems.
● Collaborate with cross-functional teams to deliver business-driven AI solutions.
Required Skills
● Strong programming skills in Python.
● Experience with vector databases (e.g., Pinecone, FAISS, ChromaDB) and graph memory systems
● Knowledge of atleast one agent development framework: Google ADK (preferred), LangChain/LangGraph/LlamaIndex, CrewAI
● Experience with LLMs, RAG, GenAI, AgenticAI Agents
● Hands-on experience with FastAPI, and REST APIs.
● Knowledge of Docker, Kubernetes, Git, CI/CD.
● Experience with AWS, Azure, or GCP.
● Experience with security compliance, monitoring and observability tools such as AWS CloudWatch, Azure Monitor, Google Cloud Monitoring.
- We are looking for experienced AI/ML Architects to join our AI Engineering service line. In this role, you will anchor the technical delivery of enterprise AI/Agentic AI projects post deal-closure. You will take over from solution architects and lead the design, build, deployment, and optimization of AI/ML systems — ensuring production-grade quality, scalability, and compliance.
- You will interface with cross-functional teams, manage engineering complexity, and ensure value realization for customers across industries such as BFSI, HLS, Manufacturing, CMT, Retail, and Energy.
Key Responsibilities
Architecture & Technical Leadership
Hands-on Engineering & Problem Solving
Required Qualifications
Education : B.Tech/M.Tech or equivalent in Computer Science, Data Science, or a related field.
Experience
● 10+ years in software architecture or engineering with 5+ years in applied AI/ML
system delivery.
● Experience in productionizing AI/ML models and building full-stack AI applications in
enterprise settings.
● Strong Python development skills; proficiency in ML/AI frameworks (PyTorch,
TensorFlow, Scikit-learn).
● Strong understanding of LLMs, RAG pipelines, vector databases (Weaviate, Qdrant,
Pinecone).
● Experience with MLOps/LLMOps tools: MLflow, Argo, KServe, Feast, Kubeflow.
● Proficiency in data pipeline engineering using Spark, Airflow, or DataFlow.
● Exposure to agent orchestration frameworks: LangChain, LangGraph, AutoGen,
CrewAI is a big plus.
● Cloud & Infrastructure
● Hands-on experience with GCP (Vertex AI, BigQuery, Document AI, AI Gateway)
and/or Azure (Azure ML, OpenAI, Synapse).
● Expertise in containerization (Docker) and orchestration (Kubernetes).
● Familiarity with Infrastructure as Code (Terraform, Pulumi, CDK).
Soft Skills
Strong architectural thinking and problem-solving in fast-paced delivery environments.
Excellent communication and collaboration skills to work across cross-functional teams and
clients.
Proactive, structured, and detail-oriented with a bias for execution.
Nice to Have
Experience in real-world deployments of Agentic AI systems or collaborative multi-agent setups.
Exposure to regulatory/ethical concerns in AI such as fairness, transparency, or bias mitigation.
Familiarity with AI observability, explainability, and governance tooling (e.g., Arize, Fiddler,
TruEra).
Key Responsibilities:
· Architectural Leadership: Design and lead the development of robust, scalable AI architectures, ensuring high performance, reliability, and security.
· Applied Mathematics & Statistics: Apply statistical analysis, numerical computation, and mathematical modeling to derive insights from large-scale data and optimize model performance.
· Deep Learning Development: Design, train, and deploy advanced Deep Learning (DL) models.
· Technical Mentorship: Mentor engineering teams on best practices for AI/ML, coding standards, and architectural design.
· Model Optimization: Optimize models for speed, efficiency, and accuracy using techniques like pruning, quantization, or GPU acceleration.
· Strategy & Innovation: Evaluate and select appropriate AI frameworks, tools, and platforms, staying abreast of cutting-edge research and industry trends.
Qualifications:
Required:
· Education: Master's or PhD in Computer Science, Applied Mathematics, Statistics, Physics, or a related quantitative field.
· Experience: 10+ years of experience in software development, with at least 3-5 years in a Applied Mathematics and Deep learning.
· AI/ML Expertise: Proven experience designing and deploying deep learning models in production using frameworks.
· Mathematics/Statistics: Strong proficiency in linear algebra, calculus, probability, and statistical methods.
· Programming Skills: Expert-level coding skills in Python (NumPy, Pandas, Scikit-learn) and experience with languages like Java or C++.
Key Competencies:
- Strategic mindset with deep operational awareness.
- Excellent communication and stakeholder management skills.
- Ability to simplify complex technical concepts for executive reporting.
- Strong leadership, people development, and cross-functional influencing skills.
Bias for action and a relentless focus on continuous improvement.
Job Description:
We are seeking a versatile and highly skilled Lead AI/ML Engineer with deep expertise in Generative AI (GenAI) and Large Language Models (LLMs). This role requires a leader who can take full ownership of the
AI lifecycle—from initial architectural design to final production execution. You will lead the development of scalable AI-powered applications, demonstrating exceptional execution skills and the ability to deliver high-performance results under pressure in demanding production environments.
Machine Learning & LLM Capability:
End-to-End ML Engineering: Build and manage comprehensive ML pipelines, including data ingestion, preprocessing, training, and evaluation using frameworks like PyTorch, TensorFlow, and Scikit-learn. Advanced LLM Systems: Design and implement sophisticated LLM-based applications such as autonomous agents, chatbots, and complex automation tools.
Generative AI Specialization: Architect and optimize Retrieval-Augmented Generation (RAG) pipelines using vector databases like FAISS, Pinecone, or Weaviate.
Model Optimization: Fine-tune open-source and proprietary models (e.g., LLaMA, GPT) using advanced techniques like LoRA, QLoRA, or instruction tuning.
Agentic Frameworks: Develop complex agentic workflows utilizing frameworks such as LangChain or LlamaIndex.
Prompt Engineering: Implement expert-level prompt engineering, tool/function calling, and structured output generation.
Project Ownership & Execution
Full Lifecycle Ownership: Take complete accountability for the full ML and GenAI lifecycle, spanning data processing, model development, monitoring, and optimization.
Architectural Leadership: Drive strategic architectural decisions for AI platforms, ensuring they are modular, scalable, and maintainable.
Execution Excellence: Write clean, high-performance Python code following strict OOP principles and manage CI/CD pipelines for seamless project execution.
Leadership & Mentoring: Act as a key technical leader, managing stakeholders and mentoring team members to ensure all project milestones are met with quality.
System Integrity: Manage model and prompt versioning, experiment tracking, and comprehensive documentation for all pipelines and workflows.
Performance Under Pressure
Production Reliability: Ensure all AI systems maintain extreme scalability and performance under heavy production workloads, including both batch and real-time processing.
High-Pressure Optimization: Rapidly optimize inference latency and system costs for ML and LLM systems to meet urgent business and technical requirements.
Proactive Problem Solving: Apply strong analytical thinking to address complex challenges such as system drift, hallucinations, and latency in fast-paced environments.
Robust Guardrails: Implement and manage strict evaluation frameworks and feedback loops to maintain system quality under stress.
Qualifications:
Bachelor’s or Master’s degree in Computer Science, AI, ML, or a related field.
Proven expertise in Python, system design, and scalable AI/ML architecture.
Deep knowledge of NLP, Computer Vision, and Deep Learning models.
Hands-on experience with Docker, Kubernetes, MLOps, and major cloud platforms (AWS, GCP, or Azure).
AuxoAI is hiring a Senior Data Scientist with strong expertise in AI, machine learning engineering (MLE), and generative AI. You will play a leading role in designing, deploying, and scaling production-grade ML systems — including large language model (LLM)-based pipelines, AI copilots, and agentic workflows. This role is ideal for someone who thrives on balancing cutting-edge research with production rigor and loves mentoring while building impact-first AI applications.
Location - Mumbai/Bangalore/Hyderabad/Gurgaon (Hybrid - 3 Days a week in Office)
Responsibilities:
- Own the full ML lifecycle: model design, training, evaluation, deployment
- Design production-ready ML pipelines with CI/CD, testing, monitoring, and drift detection
- Fine-tune LLMs and implement retrieval-augmented generation (RAG) pipelines
- Build agentic workflows for reasoning, planning, and decision-making
- Develop both real-time and batch inference systems using Docker, Kubernetes, and Spark
- Leverage state-of-the-art architectures: transformers, diffusion models, RLHF, and multimodal pipelines
- Collaborate with product and engineering teams to integrate AI models into business applications
- Mentor junior team members and promote MLOps, scalable architecture, and responsible AI best practices
Requirements
- 5+ years of experience in designing, deploying, and scaling ML/DL systems in production
- Proficient in Python and deep learning frameworks such as PyTorch, TensorFlow, or JAX
- Experience with LLM fine-tuning, LoRA/QLoRA, vector search (Weaviate/PGVector), and RAG pipelines
- Familiarity with agent-based development (e.g., ReAct agents, function-calling, orchestration)
- Solid understanding of MLOps: Docker, Kubernetes, Spark, model registries, and deployment workflows
- Strong software engineering background with experience in testing, version control, and APIs
- Proven ability to balance innovation with scalable deployment
- B.S./M.S./Ph.D. in Computer Science, Data Science, or a related field
- Bonus: Open-source contributions, GenAI research, or applied systems at scale






