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Boson AI

Boson AI

boson.ai

4 Jobs

27 Employees

About the Company

We are transforming how stories are told, knowledge is learned, and insights are gathered.

Listed Jobs

Company background Company brand
Company Name
Boson AI
Job Title
Machine Learning Engineer - Enterprise
Job Description
**Job title:** Machine Learning Engineer – Enterprise **Role Summary:** Design, develop, and deploy large‑scale language, vision, and voice models for enterprise applications. Build end‑to‑end solutions that integrate LLMs, multimodal models, and advanced retrieval systems into scalable platforms, enabling autonomous agentic workflows that interact with diverse data sources and enterprise tools. **Expectations:** - Deliver high‑quality, reliable AI systems that meet customer requirements and industry security standards. - Continuously benchmark and evaluate models, refine fine‑tuning strategies, and enhance performance through search and retrieval augmentation. - Own the full software lifecycle: specification, implementation, testing, deployment, and monitoring in production environments. - Collaborate cross‑functionally to translate business problems into technical solutions. **Key Responsibilities:** 1. Scope product specifications and architect LLM‑powered software for customer use cases. 2. Benchmark models, develop evaluation metrics, and identify weaknesses. 3. Design and deploy retrieval systems (e.g., RAG, DeepSearch) to ground LLM outputs and leverage enterprise knowledge bases. 4. Fine‑tune and align large models on domain‑specific data; optimize inference pipelines. 5. Ensure model quality, reliability, security, and scalability through rigorous testing and monitoring. 6. Integrate AI components into a unified, scalable platform with robust APIs. 7. Document architecture, code, and operational procedures. **Required Skills:** - Proficiency in Python; experience with Rust, TypeScript, or Go is a plus. - Deep knowledge of ML frameworks such as PyTorch or JAX. - Hands‑on experience with large language or multimodal models and their deployment. - Proven ability to build and optimize retrieval/search pipelines. - Strong GitHub portfolio demonstrating implementation of ML solutions. - Attention to detail in coding, testing, and security. - Familiarity with orchestration of multi‑step pipelines and workflow automation. **Required Education & Certifications:** - Bachelor’s or Master’s degree in Computer Science, Machine Learning, Artificial Intelligence, or a related quantitative field, or equivalent practical experience. - Relevant certifications in ML, data engineering, or cloud platforms are advantageous but not mandatory.
Toronto, Canada
On site
19-11-2025
Company background Company brand
Company Name
Boson AI
Job Title
Member of Technical Staff, Evaluation
Job Description
Job Title: Member of Technical Staff, Evaluation Role Summary: Design, implement, and run evaluation pipelines for large language models, analyze model behavior, and provide insights to guide model development and data annotation. Expectations: Demonstrate strong machine learning background, ability to work on high‑impact generative AI projects, and motivation to learn and contribute to foundation model research. Key Responsibilities: • Design and execute experiments to assess model capabilities • Develop efficient, clean code for evaluation workflows • Analyze and visualize results, summarize findings for cross‑functional teams • Collaborate with model training and data annotation teams to refine model performance and alignment with human values Required Skills: • Experience with prompt engineering or similar LLM interaction techniques • Proficiency in data analysis, processing, and visualization tools • Familiarity with at least one deep learning framework (e.g., PyTorch) • Ability to solve ambiguous problems creatively and communicate results clearly • Prior research or project experience in model evaluation, fine‑tuning large language or multimodal models (preferred) Required Education & Certifications: • Bachelor’s or advanced degree in Computer Science, Machine Learning, Statistics, or related field (PhD preferred for strong research track record)
Santa clara, United states
On site
20-11-2025
Company background Company brand
Company Name
Boson AI
Job Title
Network Engineer, AI/ML Infrastructure
Job Description
Job Title: Network Engineer, AI/ML Infrastructure Role Summary: Design, implement, and maintain high‑performance InfiniBand and ultra‑high‑speed Ethernet fabrics that support AI/ML workloads. Manage end‑to‑end network lifecycle—from planning and deployment to monitoring and optimization—ensuring low latency, high throughput for GPU‑to‑GPU traffic, Ceph storage connectivity, and multi‑site data center interconnects. Collaborate with HPC and ML teams to scale capacity and evaluate emerging networking technologies. Expectations: - 4+ years of production network engineering experience. - Proven knowledge of L2/L3 protocols (TCP/IP, BGP, OSPF, VLANs). - Hands‑on expertise with 100Gb+ Ethernet and InfiniBand, including RDMA, RoCE, IPoIB. - Strong background in network security (firewalls, ACLs, segmentation). - Experience with HPC network topologies and GPU‑centric bandwidth optimization. - Problem‑solving mindset with ability to troubleshoot performance bottlenecks and latency. Key Responsibilities: - Configure, maintain, and upgrade InfiniBand and high‑speed Ethernet fabrics (Mellanox, NVIDIA, Micas Networks). - Optimize RDMA and GPU‑to‑GPU communication paths for maximum throughput. - Manage network switches and implement secure segmentation using VLANs and ACLs. - Identify and resolve bottlenecks, latency issues, and packet loss. - Plan and execute network expansion, capacity planning, and technology evaluations. - Develop automation scripts/tools to streamline operations (e.g., configuration, monitoring). - Oversee infrastructure monitoring using Prometheus, Grafana, or similar. - Collaborate with storage teams to optimize Ceph cluster networking. - Design and implement multi‑site connectivity (VPN, WAN, direct interconnect). - Maintain cloud networking integrations (AWS, GCP, Azure VPC, Direct Connect, ExpressRoute). Required Skills: - L2/L3 networking, BGP, OSPF, VLAN, ACL, firewall configuration. - InfiniBand (RDMA, RoCE, IPoIB) and 100Gb+ Ethernet expertise. - Networking hardware: Broadcom Tomahawk, NVIDIA/Mellanox switches. - Network security design and implementation. - Troubleshooting and performance tuning. - Automation (Ansible, Python, shell scripting). - Monitoring & observability (Prometheus, Grafana). - Distributed storage network understanding (Ceph). - Cloud networking (VPC, VPN, Direct Connect/ExpressRoute). - Familiarity with multi‑site WAN optimization. Required Education & Certifications: - Bachelor’s degree in Computer Science, Information Technology, Electrical Engineering, or related field. - Relevant networking certifications preferred: CCNA, CCNP, JNCIP, or equivalent. - Certifications in HPC or cloud networking (e.g., AWS Certified Advanced Networking, GCP Professional Cloud Network Engineer) are a plus.
Toronto, Canada
On site
Junior
12-12-2025
Company background Company brand
Company Name
Boson AI
Job Title
Internship - MScAC
Job Description
**Job Title:** Internship – MScAC **Role Summary:** Support core research and development of large language and audio models at Boson AI as a University of Toronto MScAC student. Work directly with senior researchers on data pipelines, model training, and benchmarking for multilingual generative AI. **Expectations:** - Current enrollment in the MScAC program at the University of Toronto. - Passion for cutting‑edge ML/AI, with a focus on model behavior, alignment, and efficiency. **Key Responsibilities:** - Design and implement data extraction/annotation pipelines for multilingual LLM training using unsupervised or semi‐supervised methods. - Develop audio evaluation tools and multilingual benchmarks that capture pronunciation, style, emotion, and conversational contexts. - Create text evaluation mechanisms that probe hallucinations, stability, and constraint adherence, incorporating human‑in‑the‑loop verification. - Optimize training routines for large multimodal models, focusing on efficiency, scalability, and resource constraints. **Required Skills:** - Proficient in Python and scripting for data engineering and experimentation. - Solid grounding in machine learning, statistics, and model evaluation techniques. - Experience with unsupervised/semi‑supervised learning pipelines is a plus. - Knowledge of audio processing and evaluation metrics. - Ability to design and implement benchmarking suites for NL and audio models. - Strong analytical, experimental, and problem‑solving abilities. **Required Education & Certifications:** - Enrolled in the MScAC (Master of Science in Applied Computing) program at the University of Toronto. - Prior coursework in machine learning, data science, or related fields preferred.
Toronto, Canada
Hybrid
12-12-2025