This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more. Role Description We’re looking for a Senior Artificial Intelligence Engineer to help mature Flexion’s AI application development capabilities. Flexion is committed to providing top-tier AI application development services and is looking for an Artificial Intelligence Engineer to help us advance our capabilities. Most of the work we do is on large-scale, enterprise-wide systems (both commercial and government). What the job looks like: - Responsible for building AI applications and helping create AI application capability within Flexion. - Project work is primarily remote but may require some client on-site work estimated at <10%. - Lead AI application architectural design activities, particularly in the domain of Generative AI. - Lead AI application implementation and operations activities. - Help Flexion develop or adopt learnable AI development and deployment patterns, and avoid common pitfalls. - Coach other engineers in AI application development and operations. - Potentially fill roles adjacent to AI application development, if needed. Qualifications - At least 10 years building and operationalizing AI/ML powered applications. - At least 5 years experience working in an agile environment. - A bachelor's degree or commensurate experience. - Knowledge of lean and agile methodologies to deliver a quality product with minimal churn. - Strong communication and coaching skills. - Experience teaching and mentoring folks less seasoned with AI tools. Requirements - Production-level experience with the entire ML Lifecycle including training, fine tuning, deploying, monitoring, and retraining. - Production-level experience using and managing ML Lifecycle tooling including experiment trackers, model registry, feature stores, vector databases and deployment services. - Production-level experience with scaling services including containerization, container orchestration, load testing, autoscaling, and monitoring. - Production-level experience with scaling AI and ML specific services including the use of quantization, pruning, distributed computing on accelerated infrastructure, model compilation techniques, and inference graphs. - Production-level experience with AI cloud deployment strategies and technologies. - Production-level experience with selecting foundation or pre-trained models and finetuning them for specific use cases. - Production-level experience with optimizing models and inference pipelines. - Experience seeking out and exploring new potential opportunities to help partners advance their journey to, and into the use of AI. Benefits - The salary for this position is in the $200,000-$250,000 range annually.

This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more. Role Description As the AI Analyst, you’ll have a big mission. Responsible for assuring the Company’s standards are achieved and excellent customer service is delivered. You also understand the value of taking a moment to express gratitude to the village that helped to make it happen. As you can likely tell, 'how' things are done matters just as much as ‘what’ was done here at BH! Key Responsibilities - Identify, evaluate, and prioritize high‑impact AI use cases across operations, finance, and executive reporting to drive measurable business outcomes. - Design and deploy AI‑enabled workflows that automate repeatable analysis, reduce manual effort, and enhance decision‑making accuracy. - Develop modular prompt frameworks, reusable templates, and standardized documentation to ensure consistent, scalable AI usage across teams. - Assess emerging AI tools and platforms; translate capabilities into practical business applications with clear value, feasibility, and risk considerations. - Establish and maintain best practices for responsible AI use, including documentation standards, validation protocols, and quality controls. - Perform exploratory, operational, and ad‑hoc analyses using SQL, Excel, Power BI, and Python to support AI‑driven insights and workflow improvements. - Partner closely with the Data Science Manager to integrate AI technologies into analytical processes, dashboards, and reporting ecosystems. - Lead automation efforts for reporting, data preparation, and insight generation, ensuring consistent, efficient, and accurate outputs. - Document end‑to‑end AI‑enabled workflows and maintain a centralized repository of processes and enhancements. - Train leaders, analysts, and business users on how to effectively leverage AI tools in their daily workflows, emphasizing practical adoption and measurable impact. - Create clear, user‑friendly guides, training materials, and internal documentation to support ongoing AI education. - Serve as the primary point of contact for AI‑related questions, experimentation, and solution guidance across the organization. - Monitor usage, adoption, and performance of AI solutions; iterate and refine implementations based on user feedback and operational metrics. - Validate AI outputs to ensure accuracy, consistency, and alignment with business and compliance standards. - Maintain documentation of AI use cases, performance metrics, model behavior, and process changes to support transparency and audit readiness. - Collaborate with Software Development, IT Security, and leadership to ensure AI deployments are responsible, secure, and aligned with organizational governance frameworks. - Other duties as assigned. Qualifications - 3–5 years of experience in analytics, business analysis, or a related quantitative field, preferably in multifamily, real estate, or financial services. - Strong proficiency in SQL and Excel; experience with Python and building dashboards in Power BI is preferred. - Experience using AI tools (e.g., ChatGPT, Claude) in a professional or analytical context. - Demonstrated curiosity about emerging AI technologies and a drive to optimize processes. - Ability to translate technical concepts and capabilities into practical business applications. - Strong communication skills with the ability to train and support non‑technical stakeholders. - High level of ownership, with the ability to independently test, refine, and implement new ideas. Requirements - Seniority Level: Experienced - Industry: Property Management - Employment Type: Full-Time - Location: Remote - Work Schedule: 8am-5pm, Monday-Friday, or as needed to meet business needs. Benefits - BH is an Equal Employment Opportunity Employer. - We foster the diverse voices of our community by advocating for inclusivity, celebrating our differences, and continually evolving our practice to make BH a better place to work and live. - Our posted compensation reflects the cost of talent across multiple US geographic markets. Pay is based on a number of factors and may vary depending on job-related knowledge, skills, and experience.

This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more. Role Description At Innodata, we’re partnering with the world’s leading technology companies to build the future of generative AI and large language models (LLMs). We’re on the lookout for smart, savvy, and curious Generative AI Specialist to join our global contributor community as part of our Subject Matter Expert (SME) on Demand program. This is not a traditional full-time role. It’s a part-time, remote, flexible, project-specific opportunity designed for those who want to make a real impact—on their schedule. Whether you're a writer, linguist, educator, researcher, or just deeply passionate about language and logic, this role lets you contribute to cutting-edge AI development while maintaining control over your time. You’ll be helping LLMs learn the intricacies of language and reasoning—not just how to write, but how to think. If you’ve ever dreamed of shaping the intelligence behind tomorrow’s technology, this is your chance. This is more than just a gig—it’s a rare chance to help shape the future of AI from anywhere in the world, on your own terms. What You’ll Be Doing - Evaluation: Rating/assessing the performance of AI models or algorithms based on their output or behavior through a set of evaluative questions. - Annotation Labeling: Labeling elements of a piece of content rather than the content as a whole. - Classification: Assigning predefined categories or labels to items. - Content Quality: Evaluating the perceived quality and/or appropriateness of content. - Content Understanding: Generating labels to advance understanding of a concept, trend, etc. - Data Augmentation: Creation of additional training data for machine learning models by applying transformations to the original data. - Grading: Reviewing data and identifying whether or not a product feature works as intended based on the project's guidelines. - Identification Labeling: Labeling model outputs to identify if a piece of content is or isn't something. - Preference Ranking: Ordering or ranking items based on a set of preferences or criteria. - Prompt Generation: Creating prompts or questions that will be used to generate responses from a language model or other AI system. - Relevance Evaluation: Projects that evaluate the relevance of content based on a relevancy scale. - Response Generation: Generating responses to prompts or questions using a language model or other AI system. - Response Rewrite: Rewriting existing text while preserving the original meaning. - Response Summarization: Producing concise summaries of longer pieces of text or data. - Similarity Evaluation: Projects where content is compared in order to drive a determination. - Transcription: Converting spoken language or audio content into written text. - Translation: Converting text or spoken language from one language to another. - Data Collection: Gathering and compiling various forms of data to be used for training, evaluating, or fine-tuning the AI models. Qualifications - A Bachelor’s degree or higher in a humanities specialization is required. - Advanced degrees are strongly preferred (Master’s or PhD). - Professional or Expert level proficiency (C1/C2) in English and French. Requirements - Applicants must be legally authorized to work in the United States at the time of hire. - Innodata is unable to provide visa sponsorship now or in the future for this position. Benefits - Innodata is an equal opportunity employer and values diversity. - We do not discriminate on the basis of race, religion, color, national origin, gender, gender identity or expression, sexual orientation, age, marital status, veteran status, disability status, or any other legally protected status. - Innodata is committed to creating an inclusive environment for all employees and applicants. - If you need assistance or accommodation during the application or recruitment process due to a disability, please contact us and we will be happy to assist.

This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more. Role Description The Sr. AI Engineer, Device Intelligence will be a key member of the AI Product and Imaging Innovation team, reporting to its Sr Director. This new role is instrumental in the implementation of cutting-edge AI systems that leverage data created by Danaher devices to extract meaningful insights and dramatically improve user experience, with the goal of upleveling Danaher's devices across Life Sciences, Diagnostics and Biotechnology sectors. This position is remote in Europe or Eastern US. In this role, you will have the opportunity to: - Collaborate with the Sr Director and the broader team to develop AI-driven product improvements and create new products for Danaher devices, with an initial focus on imaging devices and the aim of extracting more valuable insights. - Design and implement advanced AI systems, including next-generation agentic workflows, LLMs and computer vision technologies, to enhance instrument automation and uplevel user capabilities. - Work closely with cross-functional and cross company teams to translate product concepts into concrete AI architectures, ensuring alignment with product success criteria and measurable KPIs. - Lead the technical implementation of AI projects of notable complexity, involving multiple functions and typically spanning multi-quarter timelines. - Drive innovation in the AI software stack, focusing on maximizing value extraction from instruments for customers through AI systems. - Collaborate with business stakeholders, technical experts, and subject matter experts to build comprehensive AI roadmaps for imaging products across various verticals. Qualifications - Bachelor's degree in computer science, electrical engineering, life sciences or a related field. An advanced degree (MS or PhD) in a relevant area (i.e. Neural Networks, Foundation Model, Agentic Workflows, Machine Learning, Computer Vision) is preferred. - Long standing experience in the Life Science, Diagnostics, Biotechnology or Tech Industry, including multiple years of experience with Agentic Systems, LLMs, and/or Multimodal AI. - Demonstrable expertise with at least 3 of the following: convolutional neural networks, foundation models, vector databases, AI evaluation methods, RAG approaches, agentic frameworks. - Proven track record of successful end-to-end implementation of AI projects in imaging applications, particularly in life sciences or healthcare domains. - Strong programming skills in languages such as Python or C++, and extensive experience with deep learning frameworks (e.g., TensorFlow, PyTorch, OpenCV) and containerization technologies (e.g., Docker, Kubernetes). - Demonstrated ability to work effectively with cross-functional teams, communicate complex technical concepts to both technical and non-technical stakeholders, and align AI development with product goals and roadmaps. - Experience with cloud platforms (e.g., AWS, Google Cloud, Azure) for large-scale image processing and familiarity with hardware acceleration technologies (e.g. TPUs, GPUs, ARM-CPUs). Requirements - Experience with regulatory processes, especially for medical devices and AI/ML-based software as a medical device (SaMD). - Familiarity with quality management systems and standards relevant to the life sciences and diagnostics industries. - Knowledge of instrument control mechanisms and how they integrate with AI systems for enhanced automation. Benefits - Comprehensive, competitive benefit programs that add value to our lives. - Health care program. - Paid time off. - Medical/dental/vision insurance. - 401(k) to eligible employees.