Data Science Specialist

Senior Data Science Engineer (AI Systems & Intelligent Automation)

ABOUT BOSENET

Bosenet builds AI-driven meeting intelligence and automated workflow systems for enterprise

environments. We combine advanced data engineering, applied machine learning, and large language

model (LLM) technologies to help organizations transform real-time collaboration and decision-making.

ROLE SUMMARY

We are seeking a Senior Data Science Engineer with 4+ years of industry experience who can

independently lead and execute AI/ML projects end-to-end. This role requires strong technical

ownership, architectural judgment, and the ability to work across data engineering, machine learning,

and production deployment.

KEY RESPONSIBILITIES

AI/ML Project Leadership

• Own AI/ML initiatives from problem definition to production deployment.

• Drive solution architecture for machine learning, NLP, and LLM-powered workflows.

• Define technical milestones, success metrics, and delivery plans.

Machine Learning, NLP & Multimodal AI

• Develop models for prediction, classification, recommendation, and text intelligence.

• Build and optimize NLP, LLM, and retrieval-augmented generation (RAG) systems.

• Work with multimodal AI, including combining audio, text, image, and document understanding.

• Apply embeddings, vector databases, CLIP-like models, or VLMs for multimodal tasks.

Computer Vision

• Develop and deploy CV models, including classification, detection, segmentation, OCR, and

document intelligence.

• Work with CNNs, transformers, and deep vision architectures (e.g., YOLO, DETR, ViT).

• Build and manage image/video datasets, labeling workflows, and evaluation pipelines.

• Integrate computer vision capabilities with NLP/LLM systems for multimodal intelligence.

Data Engineering & Pipeline Development

• Design and maintain scalable ETL/ELT pipelines for structured and unstructured data.

• Implement data quality monitoring, validation, and observability.

• Work across modern data stacks including Kafka, and cloud platforms.

Production Deployment & MLOps

• Deploy, monitor, and maintain machine learning systems in production.

• Work with versioning, CI/CD, experiment tracking, and model monitoring tools.

• Ensure reliability, reproducibility, and cost efficiency of ML services.

Cross-Functional Collaboration & Leadership

• Mentor junior engineers and contribute to team-wide best practices.

• Collaborate closely with product, engineering, and research teams.

• Provide clear technical documentation and communicate findings to stakeholders.

MINIMUM QUALIFICATIONS

• Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or related discipline.

• 4+ years of hands-on experience in applied ML, data science, or AI engineering.

• Strong proficiency in Python, SQL, and ML frameworks (scikit-learn, PyTorch, TensorFlow).

• Experience with data pipelines, feature engineering, and large-scale datasets.

• Working knowledge of LLMs, NLP techniques, and vector search.

• Experience deploying ML solutions in production environments.

PREFERRED QUALIFICATIONS

• Experience mentoring engineers or leading technical initiatives.

• Familiarity with Airflow, dbt, Kafka or equivalent data tools.

• Knowledge of RAG systems, embeddings, and advanced NLP workflows.

• Understanding of data governance, privacy, and secure ML practices.

• Experience with model evaluation frameworks and A/B testing.

WHAT SUCCESS LOOKS LIKE

• Independent delivery of a high-impact AI/ML project from concept to deployment.

• Creation of scalable models and pipelines used across engineering teams.

• Demonstrated improvement in AI accuracy, performance, or automation capabilities.

• Clear technical communication and consistent cross-team collaboration.

WHY JOIN BOSENET

• Work on cutting-edge AI systems powering enterprise meeting intelligence.

• Take full ownership of AI/ML solutions used in real-world production environments.

• Opportunity to grow into Lead or Staff-level AI engineering roles.

• Contribute to building an AI-first platform shaping the future of enterprise collaboration.