Advance state‑of‑the‑art laser ablation and automated analytical geochemistry capabilities in a world‑class research environment.
Compensation
Level A: $87,266 - $118,416 p.a. plus 17% super (PhD entry level $110,319)
Level B: $124,656 - $148,023 p.a. plus 17% super
Responsibilities
Develop, optimise and document laboratory, analytical and digital workflows for laser ablation and solution‑based mass spectrometric analyses.
Advance automation, data reduction, quality assurance, imaging and digital pipelines to generate robust, reusable and well‑curated research datasets.
Troubleshoot and improve analytical instrumentation and digital infrastructure, developing new protocols and research capabilities in response to evolving research needs.
Collaborate with researchers and external partners across academia, government and industry, contributing to research projects, funding proposals, scholarly outputs and intellectual property development.
Train and mentor students and researchers, develop standard operating procedures, and communicate research capabilities and outcomes to scientific and wider communities.
Requirements
PhD in trace element and/or isotope geochemistry or related discipline
Machine Learning Engineer focused on the quality and evaluation of ML models and AI features in creativity applications. Includes defining evaluation strategy, metrics, building datasets/infrastructure, and driving end-to-end quality.
Responsibilities
Define evaluation strategy and metrics for ML models, LLMs, and AI features, tailored to the model, the product, and its use cases.
Curate and create evaluation datasets, measure and improve dataset quality, and run iterative improvement loops so that datasets stay representative of each product.
Design, build, maintain, and optimize evaluation infrastructure at scale, with reproducible runs, tracked baselines, and comparisons between model versions.
Apply ML, LLMs, and agentic workflows to the evaluation itself, including automated judging, test generation, and analysis, to make evaluation more efficient, more accurate, and scalable.
Drive end-to-end evaluation and quality of AI features, from model checkpoints to integrated, shipping features, including triaging issues and driving them to resolution.
Apply state‑of‑the‑art deep learning techniques to search, curate, and evaluate high‑quality datasets and ground truth for autonomous vehicles.
Compensation
Your base salary will be determined based on your location, experience, and other objective job-related factors. The expected base salary ranges for this position are: 152,000 USD – 241,500 USD for Level 3; and 184,000 USD – 287,500 USD for Level 4.
Responsibilities
Stay up to date with the latest research and innovations in deep learning, implement and experiment with new ideas.
Foster collaborative partnerships with researchers and engineers, transforming innovative research into robust, industrial‑strength machine learning models.
Take approaches from initial evaluation and experimentation all the way to shipping.
Define, collect, and curate training and evaluation datasets, focusing on scenario coverage and label quality.
Develop vision‑language models and embeddings for scenario search, classification, and automated data curation.
Requirements
PhD in Computer Science
MS in Computer Science
Nice to have: background applying latest AI methods to solve computer vision and autonomous vehicle problems
Nice to have: experience with vision‑language models
Bring deep biological expertise to the data, tasks, and analyses behind our models, turning genomics and systems biology questions into computational work.
Responsibilities
Curate and integrate large biological datasets with provenance and quality control
Build reproducible bioinformatics and analysis pipelines across sequencing, functional genomics, single-cell, perturbational screening, and protein data
Help design data mixtures and sampling strategies for model training
Define biologically meaningful tasks, endpoints, and baselines with modeling and evaluation teams
Investigate model predictions and failure modes in the context of biological evidence
Requirements
PhD in Computational Biology or equivalent research or industry experience
Nice to have: large-scale biological data curation
Collaborate with faculty, operational staff, business users, and other stakeholders to develop, manage, and optimize datasets, reports, data pipelines, and systems supporting programs and projects at the HII, with a particular emphasis on the Florida Parkinson’s Disease Registry.
Responsibilities
Develop, implement, and maintain complex data processes, programs, and pipelines to integrate, transform, cleanse, and consolidate data from diverse sources for reporting, analytics, and operational use.
Create and maintain SAS, SQL, and related data processing programs to extract, subset, transform, summarize, and validate data from large and complex databases and institutional systems.
Design and implement data models, data structures, and integration processes that support reliable analytics, reporting, and data sharing.
Develop, review, enhance, publish, and schedule reports, dashboards, and analytical outputs to monitor data acquisition, data quality, project/program status, and other key performance measures.
Design and maintain processes that promote data integrity, completeness, accuracy, and consistency across datasets, reports, dashboards, and other data products.
Requirements
Bachelor's degree in Computer Science, MIS or other field involving software and analytical training
Lead the Safety AI team to build end-to-end computer vision and machine learning for Samsara’s AI dash cameras, driving real-time driver safety insights and in-cab alerts.
Compensation
$178,640—$287,100 USD
Responsibilities
Drive the Safety AI Platform Architecture
Own the technical direction for Samsara's on-device and cloud safety AI systems
Lead the transition from individual model deployments to a coherent, system-level platform
Evaluate and integrate emerging AI capabilities
Partner with product and full-stack teams to define, scope, and ship safety features
Requirements
MS or PhD in Computer Science, Electrical Engineering, or a related technical field
Nice to have: background in autonomous vehicles
Nice to have: robotics
Nice to have: fleet telematics
Nice to have: experience with safety and reliability in production
Focus on collection and processing of data on seed and plant traits using lab-based spectrometers, including organization, curation, and preliminary statistical analysis.
Compensation
The offer for this position will fall within the positions pay range based on internal equity, unit’s available budget, and the candidate’s qualifications
Responsibilities
Collection of laboratory measurements using lab-based spectrometers
Data organization and curation to ensure accurate post-collection analysis
Perform data collection on bean and coffee leaf samples
Conduct preliminary statistical analysis to ensure data integrity and examine correlations
Design follow-up experiments in consultation with research group members to augment laboratory data collection
Senior Data Scientist with 8-11 years of experience in Data Science and Machine Learning, specializing in NLP, Generative AI, LLMs, MLOps, and AI solution architecture, responsible for designing, implementing, and optimizing AI solutions for enterprise use cases.
Responsibilities
Contribute to the design and implementation of state-of-the-art AI solutions
Assist in the development and implementation of AI models and systems, leveraging techniques such as Language Models (LLMs) and generative AI
Collaborate with stakeholders to identify business opportunities and define AI project goals
Stay updated with the latest advancements in generative AI techniques, such as LLMs, and evaluate their potential applications in solving enterprise challenges
Utilize generative AI techniques, such as LLMs, to develop innovative solutions for enterprise industry use cases
Requirements
Bachelor's or Master's degree in Computer Science, Engineering, or a related field
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