Responsibilities:

• Develop innovative solutions using machine learning and advanced statistics to solve business problems.
• Influence the AI roadmap of the biggest P&C insurer in Canada.
• Keep pace with new approaches and trends and use them in your own solutions.
• Work within a multi-disciplinary environment mixing people from data science, software engineering, actuarial science, business and design.
• Share knowledge with interns and other data scientist to grow, as a team All this, while keeping a good work-life balance.

Requirements & Skills:

• A bachelor’s degree in a quantitative discipline such as mathematics, science, engineering, statistics, AI, computer science, or a related field. MSc and/or PhD are an asset.
• 2+ years of experience in the field of data science, machine learning, and advanced statistics solving business problems.
• Programming experience in languages such as Python or R as well as knowledge of software engineering best practice or a strong desire to learn it.
• Familiar with the underlying theory of machine learning (supervised, unsupervised,d and reinforcement learning).
• The commitment to be a great, collaborative teammate.
• Unlimited curiosity and a passion to challenge the status quo.
• Ability to focus on vaguely defined issues requiring the application of a creative approach.
• Strong communication, time management, and work organization skills.

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Responsibilities:

• Data Analysis and Modeling. Utilize statistical methods and machine learning algorithms to analyze complex data sets, build predictive models, and derive actionable insights.
• Data Visualization and Communication. Create clear and compelling data visualizations and reports to effectively communicate findings and recommendations to stakeholders.
• Collaboration and Strategy Development. Work with cross-functional teams to integrate data science solutions into business strategies, providing expertise in data-driven decision-making and innovation.

The post Data Scientist, NTT DATA appeared first on AI Jobs Latest.

Responsibilities:

• Participate directly in every part of the development life cycle of ML models: conception, implementation, automated testing, deployment, monitoring, etc.
• Investigate, analyze, and improve the performance of our models and systems – including meeting critical SLOs for training models at scale and low-latency inference.
• Maintain and improve several of our most important client-facing product features.
• Facilitate the adoption and utilization of ML platform and observability resources and guidelines to improve operational efficiency and service reliability.
• Engage with your community of peers to challenge the status quo, improve our shared ways of working, and influence overall architecture decisions.
• Learn, utilize, and evolve our data and tech stack which includes Python, AWS, Kubernetes, Pytorch, Terraform, Snowflake, Honeycomb, and others

Requirements & Skills:

• You have 5+ years of Machine Learning industry experience.
• You have operationalized, instrumented, and supported AI models in production at a non-trivial scale before
• You are fluent in good data and software engineering practices, and you are able to develop the tools and culture which enable your team to deliver reliable production code in an efficient manner.
• You enjoy collaborating with scientists on a daily basis to understand their pain points and figure out how to improve their tools and increase their efficiency. You also have experience working in cross-functional teams.

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Responsibilities:

• Brainstorm, design and develop the company’s AI initiatives and roadmaps
• Formulate the business problem into AI and Machine Learning tasks
• Working with different types of data including computer logs, errors, natural languages, and more
• Extract, transform, load structured and unstructured text data
• Perform AI and machine learning experiments methodically, and conduct data and error analysis to improve models
• Document findings, approaches and present the results to the team
• Optimize algorithms and prototypical solutions, such as hyperparameter search, model fine-tuning, etc.
• Collaborate with the engineering team to implement (build, test and deploy) the ML models
• Create unit, integration, end-to-end, and/or performance tests.
• Keep current with technology and industry developments and be on the lookout for new approaches and opportunities to integrate them into the existing solutions

Requirements & Skills:

• Have strong analytical and problem-solving skills, and be willing to dive deep to find creative solutions.
• Have a passion for developing new and innovative solutions with AI, machine learning, and statistical approaches.
• Have an entrepreneurial spirit and love to work in a fast-growing start-up environment, where you will meet like-minded people and celebrate successes.
• BSc or MSc degree in computer science, engineering, statistics, applied mathematics, or related quantitative discipline.
• Ability to synthesize information from multiple sources and act as a thought leaders to design creative solutions.
• Experience in ML/AI solution architecture is an asset.
• Strong track records in building MLOps and productionizing ML/AI solutions in Azure cloud (or AWS). Familiarity with ML flow is a plus.
• Experience in data mining, machine learning, and/or statistical analysis. Knowledge of NLP approaches is an asset.
• Strong experience in Python and knowledge of SQL is a plus.
• Familiarity with modern machine learning packages such as NumPy, SciPy, Pandas, Matplotlib, seaborn, Scrapy, scikit-learn, etc. Experience with Deep Learning packages such as Pytorch or TensorFlow is an asset.
• Knowledge of the Cross Industry Standard Process for Data Mining(CRISP-DM) or similar data-science lifecycle.
• Experience building custom integrations between cloud-based systems using APIs.
• Experience developing and maintaining ML systems built with open-source tools.
• Experience developing with containers and Kubernetes in cloudcomputing environments.
• Basic knowledge of agile software development (e.g. versioncontrol, kanban processes, and cloud deployment).
• Team player. Comfort working in a dynamic group with open problems to solve.

The post ML Engineer/Data Engineer, Railtown AI appeared first on AI Jobs Latest.

Responsibilities:

• Be part of a team working on building out scalable infrastructure to train, evaluate, deploy, perform inference, and monitor our ML models
• Build, deploy, and maintain generative AI services & applications
• Create data systems to collect, clean, label, and store data used for model features
• Deploy and manage various applications in our Kubernetes clusters
• Collaborate with Machine Learning engineers to build & support state-of-the-art experimentation platforms, training framework,s and associated tools
• Work with stakeholders on requirements and solutions for ML infrastructure
• And of course, you will be coding every day!

Requirements & Skills:

• 5+ years of industry experience building production-level ML platforms and infrastructure, including experience building ML systems/pipelines from the ground up.
• Ability to write high-quality code in Python, Java, or Scala
• Experience building production-ready RESTful APIs, as well as having scaled platforms in production to a large number of users.
• A desire to own large parts of an ML Platform, with a strong understanding of ML models & principles.
• Experience working with containers and deploying applications to Kubernetes
• Experience with LLMs and building infrastructure to support LLM applications
• Experience with relational and low-latency databases
• Experience with transforming data in both batch and streaming contexts
• A desire to learn new technologies quickly, and a proven track record of making quality vs. deadline tradeoffs in fast-paced environments.
• Ability to scope out a large project and manage it through project delivery
• Strong communication skills and ability to generate consensus and buy-in within the team
• Organizational skills and the ability to simplify complex problems and prioritize what matters most for the sake of the team and the business
• Experience working with highly sensitive data in a healthcare environment
• Experience working with ML frameworks such as PyTorch, SciKit-learn, XGboost
• Experience working with ML Ops tools such as MLFlow, Kubeflow, AWS Sagemaker
• Experience building solutions on cloud infrastructure, particularly AWS

The post Sr. AI/ML Infrastructure Engineer, Lyra Health appeared first on AI Jobs Latest.

Responsibilities:

• You will help us implement, test, characterize, and refine novel elements of a machine-learning architecture designed from the ground up to optimize the properties of small-molecule drugs; continually improve the robustness of our existing code base; and apply our pipeline to new drug targets.

Requirements & Skills:

• Ph.D. in machine learning or related discipline.
• Extensive publication record in top conferences (NeurIPS, ICML, ICLR, CVPR, etc.).
• Five or more years of experience developing robust code on larger projects, including code review, refactoring, unit testing, version control, etc.
• Expertise in Python and PyTorch.
• Intellectual curiosity and drive to excel.

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