Add job postings generated by script

job-postings/12-01-2025/1.txt

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+About Us
+
+We are a cutting-edge, fully remote team disrupting the world of algorithmic trading by leveraging large language models (LLMs).
+
+Our mission is to develop fully autonomous trading agents and make advanced AI more accessible.
+
+We foster an open and collaborative environment, valuing diversity, continuous learning, and intellectual curiosity.
+
+Role Summary
+
+
+As a Senior Quantitative Researcher, you will be responsible for researching, developing, and implementing state-of-the-art algorithms to optimize the performance of LLMs for algorithmic trading. This includes:
+
+Designing and developing innovative methods to enhance LLM architectures for financial market prediction and decision-making.
+Building scalable and efficient pipelines for training and deploying LLMs.
+Collaborating with software developers and data scientists to improve trading infrastructure.
+Analyzing historical and real-time market data to identify trading opportunities and enhance strategy performance.
+Optimizing and monitoring live trading algorithms to ensure consistent profitability.
+Staying ahead of market trends, industry regulations, and emerging technologies.
+Publishing research papers and presenting findings at top-tier conferences.
+Ideal Candidate Profile
+
+
+Education:
+
+PhD or Master's Degree in Computer Science, Statistics, Mathematics, Electrical Engineering, Physics, or related fields.
+Technical Expertise:
+
+Proven expertise in natural language processing (NLP) and generative AI.
+Strong background in deep learning, particularly in LLM architectures.
+Experience with large-scale LLM training frameworks such as PyTorch or TensorFlow.
+Proficiency with GPU acceleration (CUDA) and distributed computing.
+Solid programming skills in Python or C++ and familiarity with frameworks like Hugging Face or similar.
+Strong mathematical understanding of AI principles and their integration into LLMs.
+Experience with algorithmic trading platforms and statistical modeling.
+Strong knowledge of market microstructure and financial instruments.
+Proven success in developing and executing trading strategies.
+Understanding of risk management practices in trading.
+Skills and Mindset:
+
+Strong analytical and problem-solving capabilities.
+Self-driven, innovative, and collaborative.
+Ability to work independently in a remote, cross-cultural environment.
+Ability to thrive in a fast-paced, results-driven environment.
+Demonstrated ability to generate impactful research in academic and professional pursuits.
+What We Offer
+
+The opportunity to work on groundbreaking LLM technologies in the exciting field of algorithmic trading.
+Fully remote work environment with flexible hours.
+Competitive salary and equity package.
+Regular virtual team-building events and knowledge-sharing sessions.
+Support for continued learning, conference attendance, and professional development.
+A chance to make a significant impact in a rapidly growing field.
+To Apply
+
+
+Interested candidates should submit their resume, project portfolio, and publication list.

job-postings/12-01-2025/10.txt

@@ -0,0 +1,29 @@
+Overview
+
+In this role, you’ll be embedded inside a vibrant team of data scientists. You’ll be expected to help conceive, code, and deploy data science models at scale using the latest industry tools. Important skills include data wrangling, feature engineering, developing models, and testing metrics. You can expect to...
+
+What you'll bring
+
+BS, MS, or PhD degree in Computer Science or related field, or equivalent practical experience.
+6+ years of experience
+Knowledgeable with Data Science tools and frameworks (i.e. Python, Scikit, NLTK, Numpy, Pandas, TensorFlow, Keras, R, Spark).
+Basic knowledge of machine learning techniques (i.e. classification, regression, and clustering).
+Understand machine learning principles (training, validation, etc.)
+Knowledge of data query and data processing tools (i.e. SQL)
+Computer science fundamentals: data structures, algorithms, performance complexity, and implications of computer architecture on software performance (e.g., I/O and memory tuning).
+Software engineering fundamentals: version control systems (i.e. Git, Github) and workflows, and ability to write production-ready code.
+Experience deploying highly scalable software supporting millions or more users
+Experience with GPU acceleration (i.e. CUDA and cuDNN)
+Experience with integrating applications and platforms with cloud technologies (i.e. AWS and GCP)
+Strong oral and written communication skills. Ability to conduct meetings and make professional presentations, and to explain complex concepts and technical material to non-technical users
+
+How you will lead
+
+Discover data sources, get access to them, import them, clean them up, and make them machine learning-ready.
+Work with data scientists to create and refine features from the underlying data and build pipelines to train and deploy models.
+Partner with data scientists to understand, implement, refine and design machinelearning and other algorithms.
+Run regular A/B tests, gather data, perform statistical analysis, draw conclusions on the impact of your models.
+Work cross functionally with product managers, data scientists and product engineers, and communicate results to peers and leaders.
+Explore new technology shifts in order to determine how they might connect with the customer benefits we wish to deliver
+
+Intuit provides a competitive compensation package with a strong pay for performance rewards approach. The expected base pay range for this position is New York $161,500 – 219,000, Bay Area California $161,500 – 219,000, Southern California $149,500 – 202,000. This position will be eligible for a cash bonus, equity rewards and benefits, in accordance with our applicable plans and programs (see more about our compensation and benefits at Intuit®: Careers | Benefits). Pay offered is based on factors such as job-related knowledge, skills, experience, and work location. To drive ongoing pay equity for employees, Intuit conducts regular comparisons across categories of ethnicity and gender.

job-postings/12-01-2025/2.txt

@@ -0,0 +1,20 @@
+Actualmente nos encontramos en la búsqueda del mejor talento para ocupar el puesto de Especialista Junior en Google Cloud y Machine Learning. 
+
+Perfil: Ing. De Sistemas o afines. 
+
+Requisitos:
+•Conocimientos en Google Cloud Platform (especialmente en AI Platform).
+•Experiencia con modelos de machine learning y AutoML.
+•Familiaridad con lenguajes de programación como Python.
+•Habilidades en el manejo de datos y almacenamiento en la nube.
+
+Responsabilidades:
+•Desarrollar y entrenar modelos de machine learning usando Google AI Platform.
+•Gestionar y analizar grandes volúmenes de datos en Google Cloud.
+•Implementar y mantener modelos en producción.
+
+Competencias:
+•Capacidad para resolver problemas.
+•Habilidad para trabajar en equipo y comunicarse efectivamente.
+
+**Los interesados enviar su CV y certiadulto al siguiente correo: [email protected] // asunto: Especialista Junior en Google Cloud y Machine Learning. **

job-postings/12-01-2025/3.txt

@@ -0,0 +1,31 @@
+Overview
+
+Come join Intuit as a Staff Machine Learning Engineer!
+
+In this role, you’ll work alongside data scientists and machine learning engineers to create AI-powered experiences. You’ll be expected to help conceive, code, and deploy models at scale using the latest industry tools. Important skills include creating data pipelines, developing and deploying models, and machine learning operations.
+
+What you'll bring
+
+BS, MS, or PhD degree in Computer Science or related field, or equivalent work experience.
+6+ years of experience
+Knowledgeable with Data Science tools and frameworks (i.e. Python, Scikit, NLTK, Numpy, Pandas, TensorFlow, Keras, R, Spark).
+Knowledge of machine learning techniques (i.e. classification, regression, and clustering).
+Understand machine learning principles (training, validation, etc.)
+Knowledge of data query and data processing tools (i.e. SQL)
+Computer science fundamentals: data structures, algorithms, performance complexity, and implications of computer architecture on software performance (e.g., I/O and memory tuning).
+Software engineering fundamentals: version control systems (i.e. Git, Github) and workflows, and ability to write production-ready code.
+Experience deploying highly scalable software supporting millions or more users
+Experience with integrating applications and platforms with cloud technologies (i.e. AWS and GCP)
+Strong oral and written communication skills. Ability to conduct meetings and make professional presentations, and to explain complex concepts and technical material to non-technical users
+
+How you will lead
+
+Work with data scientists to create and refine features from the underlying data and build pipelines to train and deploy models.
+Build "machine learning ready" feature pipelines.
+Partner with data scientists to understand, implement, refine and design machine learning and other algorithms.
+Run regular A/B tests, gather data, and draw conclusions on the impact of your models.
+Monitor and maintain production models.
+Work cross functionally with product managers, data scientists and product engineers, and communicate results to peers and leaders.
+Explore new technology shifts in order to determine how they might connect with the customer benefits we wish to deliver.
+
+Intuit provides a competitive compensation package with a strong pay for performance rewards approach. The expected base pay range for this position is New York $191,000 – 258,500, Bay Area California $191,000 – 258,500, Southern California $180,000 – 243,500. This position will be eligible for a cash bonus, equity rewards and benefits, in accordance with our applicable plans and programs (see more about our compensation and benefits at Intuit®: Careers | Benefits). Pay offered is based on factors such as job-related knowledge, skills, experience, and work location. To drive ongoing pay equity for employees, Intuit conducts regular comparisons across categories of ethnicity and gender.

job-postings/12-01-2025/4.txt

@@ -0,0 +1,29 @@
+Overview
+
+In this role, you’ll be embedded inside a vibrant team of data scientists. You’ll be expected to help conceive, code, and deploy data science models at scale using the latest industry tools. Important skills include data wrangling, feature engineering, developing models, and testing metrics. You can expect to...
+
+What you'll bring
+
+BS, MS, or PhD degree in Computer Science or related field, or equivalent practical experience.
+6+ years of experience
+Knowledgeable with Data Science tools and frameworks (i.e. Python, Scikit, NLTK, Numpy, Pandas, TensorFlow, Keras, R, Spark).
+Basic knowledge of machine learning techniques (i.e. classification, regression, and clustering).
+Understand machine learning principles (training, validation, etc.)
+Knowledge of data query and data processing tools (i.e. SQL)
+Computer science fundamentals: data structures, algorithms, performance complexity, and implications of computer architecture on software performance (e.g., I/O and memory tuning).
+Software engineering fundamentals: version control systems (i.e. Git, Github) and workflows, and ability to write production-ready code.
+Experience deploying highly scalable software supporting millions or more users
+Experience with GPU acceleration (i.e. CUDA and cuDNN)
+Experience with integrating applications and platforms with cloud technologies (i.e. AWS and GCP)
+Strong oral and written communication skills. Ability to conduct meetings and make professional presentations, and to explain complex concepts and technical material to non-technical users
+
+How you will lead
+
+Discover data sources, get access to them, import them, clean them up, and make them machine learning-ready.
+Work with data scientists to create and refine features from the underlying data and build pipelines to train and deploy models.
+Partner with data scientists to understand, implement, refine and design machinelearning and other algorithms.
+Run regular A/B tests, gather data, perform statistical analysis, draw conclusions on the impact of your models.
+Work cross functionally with product managers, data scientists and product engineers, and communicate results to peers and leaders.
+Explore new technology shifts in order to determine how they might connect with the customer benefits we wish to deliver
+
+Intuit provides a competitive compensation package with a strong pay for performance rewards approach. The expected base pay range for this position is New York $161,500 – 219,000, Bay Area California $161,500 – 219,000, Southern California $149,500 – 202,000. This position will be eligible for a cash bonus, equity rewards and benefits, in accordance with our applicable plans and programs (see more about our compensation and benefits at Intuit®: Careers | Benefits). Pay offered is based on factors such as job-related knowledge, skills, experience, and work location. To drive ongoing pay equity for employees, Intuit conducts regular comparisons across categories of ethnicity and gender.

job-postings/12-01-2025/5.txt

@@ -0,0 +1,29 @@
+Overview
+
+In this role, you’ll be embedded inside a vibrant team of data scientists. You’ll be expected to help conceive, code, and deploy data science models at scale using the latest industry tools. Important skills include data wrangling, feature engineering, developing models, and testing metrics. You can expect to...
+
+What you'll bring
+
+BS, MS, or PhD degree in Computer Science or related field, or equivalent practical experience.
+6+ years of experience
+Knowledgeable with Data Science tools and frameworks (i.e. Python, Scikit, NLTK, Numpy, Pandas, TensorFlow, Keras, R, Spark).
+Basic knowledge of machine learning techniques (i.e. classification, regression, and clustering).
+Understand machine learning principles (training, validation, etc.)
+Knowledge of data query and data processing tools (i.e. SQL)
+Computer science fundamentals: data structures, algorithms, performance complexity, and implications of computer architecture on software performance (e.g., I/O and memory tuning).
+Software engineering fundamentals: version control systems (i.e. Git, Github) and workflows, and ability to write production-ready code.
+Experience deploying highly scalable software supporting millions or more users
+Experience with GPU acceleration (i.e. CUDA and cuDNN)
+Experience with integrating applications and platforms with cloud technologies (i.e. AWS and GCP)
+Strong oral and written communication skills. Ability to conduct meetings and make professional presentations, and to explain complex concepts and technical material to non-technical users
+
+How you will lead
+
+Discover data sources, get access to them, import them, clean them up, and make them machine learning-ready.
+Work with data scientists to create and refine features from the underlying data and build pipelines to train and deploy models.
+Partner with data scientists to understand, implement, refine and design machinelearning and other algorithms.
+Run regular A/B tests, gather data, perform statistical analysis, draw conclusions on the impact of your models.
+Work cross functionally with product managers, data scientists and product engineers, and communicate results to peers and leaders.
+Explore new technology shifts in order to determine how they might connect with the customer benefits we wish to deliver
+
+Intuit provides a competitive compensation package with a strong pay for performance rewards approach. The expected base pay range for this position is New York $161,500 – 219,000, Bay Area California $161,500 – 219,000, Southern California $149,500 – 202,000. This position will be eligible for a cash bonus, equity rewards and benefits, in accordance with our applicable plans and programs (see more about our compensation and benefits at Intuit®: Careers | Benefits). Pay offered is based on factors such as job-related knowledge, skills, experience, and work location. To drive ongoing pay equity for employees, Intuit conducts regular comparisons across categories of ethnicity and gender.

job-postings/12-01-2025/6.txt

@@ -0,0 +1,29 @@
+Overview
+
+In this role, you’ll be embedded inside a vibrant team of data scientists. You’ll be expected to help conceive, code, and deploy data science models at scale using the latest industry tools. Important skills include data wrangling, feature engineering, developing models, and testing metrics. You can expect to...
+
+What you'll bring
+
+BS, MS, or PhD degree in Computer Science or related field, or equivalent practical experience.
+6+ years of experience
+Knowledgeable with Data Science tools and frameworks (i.e. Python, Scikit, NLTK, Numpy, Pandas, TensorFlow, Keras, R, Spark).
+Basic knowledge of machine learning techniques (i.e. classification, regression, and clustering).
+Understand machine learning principles (training, validation, etc.)
+Knowledge of data query and data processing tools (i.e. SQL)
+Computer science fundamentals: data structures, algorithms, performance complexity, and implications of computer architecture on software performance (e.g., I/O and memory tuning).
+Software engineering fundamentals: version control systems (i.e. Git, Github) and workflows, and ability to write production-ready code.
+Experience deploying highly scalable software supporting millions or more users
+Experience with GPU acceleration (i.e. CUDA and cuDNN)
+Experience with integrating applications and platforms with cloud technologies (i.e. AWS and GCP)
+Strong oral and written communication skills. Ability to conduct meetings and make professional presentations, and to explain complex concepts and technical material to non-technical users
+
+How you will lead
+
+Discover data sources, get access to them, import them, clean them up, and make them machine learning-ready.
+Work with data scientists to create and refine features from the underlying data and build pipelines to train and deploy models.
+Partner with data scientists to understand, implement, refine and design machinelearning and other algorithms.
+Run regular A/B tests, gather data, perform statistical analysis, draw conclusions on the impact of your models.
+Work cross functionally with product managers, data scientists and product engineers, and communicate results to peers and leaders.
+Explore new technology shifts in order to determine how they might connect with the customer benefits we wish to deliver
+
+Intuit provides a competitive compensation package with a strong pay for performance rewards approach. The expected base pay range for this position is New York $161,500 – 219,000, Bay Area California $161,500 – 219,000, Southern California $149,500 – 202,000. This position will be eligible for a cash bonus, equity rewards and benefits, in accordance with our applicable plans and programs (see more about our compensation and benefits at Intuit®: Careers | Benefits). Pay offered is based on factors such as job-related knowledge, skills, experience, and work location. To drive ongoing pay equity for employees, Intuit conducts regular comparisons across categories of ethnicity and gender.

job-postings/12-01-2025/7.txt

@@ -0,0 +1,36 @@
+Overview
+
+Intuit Mailchimp is a leading marketing platform for small businesses. We empower millions of customers around the world to build their brands and grow their companies with a suite of marketing automation, multichannel campaigns, CRM, and analytics tools.
+
+Data Engineering is a highly functional distributed team, supporting data science and product teams for Mailchimp. We create paved paths for classical machine learning patterns and for interaction with large language models. We enable AI-driven product features and enable our leaders to make informed business decisions through data. We build and maintain platforms and services providing access to analytical data and machine-learned predictions.
+
+ML Platform is an established capability for Mailchimp and Intuit. We are looking to accelerate our usage of both tool sets for classical machine learning patterns in addition to interaction with large language models.
+
+The Senior Software Engineer will have experience with cloud architecture and Python. The ideal candidate loves to learn new things, ask questions, and collaborates well with others to discover and build out the best solution.
+
+Intuit Mailchimp is a hybrid workplace, giving employees the opportunity to collaborate in person with team members in our Atlanta and Brooklyn offices two or more days per week.
+
+What you'll bring
+
+We’d Love To Hear From You If
+
+You have a passion for cloud engineering and platform development.
+You have a level of resourcefulness that sets you apart from your peers.
+You collaborate well with others to discover and build out the best solution. 
+You have a collaborative attitude to not only share ideas and resources, but to help others meet their goals and grow the collective knowledge of the team.
+You have an ability to interact with well-documented web APIs through scripting and code.
+You have a Bachelor’s Degree in Computer Science, Machine Learning, Data Science, or equivalent experience.
+You have experience with Python, Cloud Dev, Docker, Kubernetes, experience with popular ML libraries like sk-learn and PyTorch.
+You have experience with ETL and distributed computing tools such as Spark, SQL, etc.
+It is a bonus if you have experience in Java, Airlow, Kubeflow, MLFlow, BigQuery
+
+How you will lead
+
+What You’ll Do
+
+Develop machine learning patterns for building and training classical machine learning models and interaction with large language models.
+Developing ingestion/pre-compute jobs using container orchestration tools ( Airflow )
+Collaborate with the Data Science and Machine Learning teams to gather requirements, and work through implementing solutions
+Iterate on Mailchimp’s Prompt Management platform to accelerate the ability of our product teams to use LLM’s effectively and responsibly. 
+
+Intuit provides a competitive compensation package with a strong pay for performance rewards approach. The expected base pay range for this position is New York $152,000 - $205,500. This position will be eligible for a cash bonus, equity rewards and benefits, in accordance with our applicable plans and programs (see more about our compensation and benefits at Intuit®: Careers | Benefits). Pay offered is based on factors such as job-related knowledge, skills, experience, and work location. To drive ongoing pay equity for employees, Intuit conducts regular comparisons across categories of ethnicity and gender.

job-postings/12-01-2025/8.txt

@@ -0,0 +1,36 @@
+Overview
+
+Intuit Mailchimp is a leading marketing platform for small businesses. We empower millions of customers around the world to build their brands and grow their companies with a suite of marketing automation, multichannel campaigns, CRM, and analytics tools.
+
+Data Engineering is a highly functional distributed team, supporting data science and product teams for Mailchimp. We create paved paths for classical machine learning patterns and for interaction with large language models. We enable AI-driven product features and enable our leaders to make informed business decisions through data. We build and maintain platforms and services providing access to analytical data and machine-learned predictions.
+
+ML Platform is an established capability for Mailchimp and Intuit. We are looking to accelerate our usage of both tool sets for classical machine learning patterns in addition to interaction with large language models.
+
+The Senior Software Engineer will have experience with cloud architecture and Python. The ideal candidate loves to learn new things, ask questions, and collaborates well with others to discover and build out the best solution.
+
+Intuit Mailchimp is a hybrid workplace, giving employees the opportunity to collaborate in person with team members in our Atlanta and Brooklyn offices two or more days per week.
+
+What you'll bring
+
+We’d Love To Hear From You If
+
+You have a passion for cloud engineering and platform development.
+You have a level of resourcefulness that sets you apart from your peers.
+You collaborate well with others to discover and build out the best solution. 
+You have a collaborative attitude to not only share ideas and resources, but to help others meet their goals and grow the collective knowledge of the team.
+You have an ability to interact with well-documented web APIs through scripting and code.
+You have a Bachelor’s Degree in Computer Science, Machine Learning, Data Science, or equivalent experience.
+You have experience with Python, Cloud Dev, Docker, Kubernetes, experience with popular ML libraries like sk-learn and PyTorch.
+You have experience with ETL and distributed computing tools such as Spark, SQL, etc.
+It is a bonus if you have experience in Java, Airlow, Kubeflow, MLFlow, BigQuery
+
+How you will lead
+
+What You’ll Do
+
+Develop machine learning patterns for building and training classical machine learning models and interaction with large language models.
+Developing ingestion/pre-compute jobs using container orchestration tools ( Airflow )
+Collaborate with the Data Science and Machine Learning teams to gather requirements, and work through implementing solutions
+Iterate on Mailchimp’s Prompt Management platform to accelerate the ability of our product teams to use LLM’s effectively and responsibly. 
+
+Intuit provides a competitive compensation package with a strong pay for performance rewards approach. The expected base pay range for this position is New York $152,000 - $205,500. This position will be eligible for a cash bonus, equity rewards and benefits, in accordance with our applicable plans and programs (see more about our compensation and benefits at Intuit®: Careers | Benefits). Pay offered is based on factors such as job-related knowledge, skills, experience, and work location. To drive ongoing pay equity for employees, Intuit conducts regular comparisons across categories of ethnicity and gender.

job-postings/12-01-2025/9.txt

@@ -0,0 +1,31 @@
+Overview
+
+Come join Intuit as a Staff Machine Learning Engineer!
+
+In this role, you’ll work alongside data scientists and machine learning engineers to create AI-powered experiences. You’ll be expected to help conceive, code, and deploy models at scale using the latest industry tools. Important skills include creating data pipelines, developing and deploying models, and machine learning operations.
+
+What you'll bring
+
+BS, MS, or PhD degree in Computer Science or related field, or equivalent work experience.
+6+ years of experience
+Knowledgeable with Data Science tools and frameworks (i.e. Python, Scikit, NLTK, Numpy, Pandas, TensorFlow, Keras, R, Spark).
+Knowledge of machine learning techniques (i.e. classification, regression, and clustering).
+Understand machine learning principles (training, validation, etc.)
+Knowledge of data query and data processing tools (i.e. SQL)
+Computer science fundamentals: data structures, algorithms, performance complexity, and implications of computer architecture on software performance (e.g., I/O and memory tuning).
+Software engineering fundamentals: version control systems (i.e. Git, Github) and workflows, and ability to write production-ready code.
+Experience deploying highly scalable software supporting millions or more users
+Experience with integrating applications and platforms with cloud technologies (i.e. AWS and GCP)
+Strong oral and written communication skills. Ability to conduct meetings and make professional presentations, and to explain complex concepts and technical material to non-technical users
+
+How you will lead
+
+Work with data scientists to create and refine features from the underlying data and build pipelines to train and deploy models.
+Build "machine learning ready" feature pipelines.
+Partner with data scientists to understand, implement, refine and design machine learning and other algorithms.
+Run regular A/B tests, gather data, and draw conclusions on the impact of your models.
+Monitor and maintain production models.
+Work cross functionally with product managers, data scientists and product engineers, and communicate results to peers and leaders.
+Explore new technology shifts in order to determine how they might connect with the customer benefits we wish to deliver.
+
+Intuit provides a competitive compensation package with a strong pay for performance rewards approach. The expected base pay range for this position is New York $191,000 – 258,500, Bay Area California $191,000 – 258,500, Southern California $180,000 – 243,500. This position will be eligible for a cash bonus, equity rewards and benefits, in accordance with our applicable plans and programs (see more about our compensation and benefits at Intuit®: Careers | Benefits). Pay offered is based on factors such as job-related knowledge, skills, experience, and work location. To drive ongoing pay equity for employees, Intuit conducts regular comparisons across categories of ethnicity and gender.