Tiger Analytics is looking for experienced Machine Learning Engineers to join our fast-growing advanced analytics consulting firm. Our employees bring deep expertise in Machine Learning, Data Science, and AI. We are the trusted analytics partner for multiple Fortune 500 companies, enabling them to generate business value from data. Our business value and leadership has been recognized by various market research firms, including Forrester and Gartner. We are looking for top-notch talent as we continue to build the best global analytics consulting team in the world. You will be responsible for: <ul> <li>Providing solutions for the deployment, execution, validation, monitoring, and improvement of data science solutions</li> <li>Creating Scalable Machine Learning systems that are highly performant</li> <li>Building reusable production data pipelines for implemented machine learning models</li> <li>Writing production-quality code and libraries that can be packaged as containers, installed and deployed</li> </ul> You will collaborate with cross-functional teams and business partners and will have the opportunity to drive current and future strategy by leveraging your analytical skills as you ensure business value and communicate the results. Requirements Essential Functions <li> Support ML projects from strategy through implementation and on-going improvements. </li><li> Perform data collection, analysis, validation, cleansing, developing software in support of multiple </li> machine learning workflows, integrating / deployment of code in a large-scale productionnvironments and reporting. <li> Designs, codes, tests, debugs, and documents ML code - models, ETL processes, SQL queries, and </li> stored procedures. <li> Extracts and analyzes data from various structured and unstructured sources, including databases, </li> files, data lakes and external APIs/websites. <li> Responds to data inquiries from various groups within client's organization. </li><li> Requires experience with relational databases, document databases (NOSQL) and knowledge of </li> query tools and/or statistical software. <li> Responsible for other duties/projects as assigned by business management / leadership. </li> Qualifications Minimum Required <li> 7 plus years of experience in statistical modeling, data mining, analytics techniques, machine </li> learning software development and reporting. <li> 5 plus years of applied experience in building / deploying Machine Learning solutions using </li> various supervised/unsupervised ML algorithms such as Linear/Logistic Regression, Support Vector Machines, (Deep) Neural Networks, Random Forest, etc., and key parameters that affect their performance. <li> 5 plus years of hands-on experience with Python and/or R programming and statistical </li> packages, and ML libraries such as scikit-learn, TensorFlow, PyTorch, etc. <li> 3 plus years of experience in building use cases / solutions especially around AI/ </li> based on Cloud infrastructure and services such as Azure,GCP,AWS cloud platforms and Onpremise environments <li> Expertise with SQL, noSQL, Python, R, Javascript programming languages and big data </li> environments (such as Splunk, Hadoop, Spark, Flink, Stream Analytics, Kafka, Docker, Kubernetes etc.) <li> Experience developing experimental and analytic plans for data modeling processes, using </li> strong baselines, and determining cause and effect relations. <li> Understanding of relevant statistical measures such as confidence intervals, significance of error </li> measurements, development and evaluation data sets, etc. in data analysis projects. <li> Expertise with scaling pilot machine learning solutions to a large scale production environment using databricks </li><li> Expertise with visualization tools such as PowerBI, D3JS etc. </li><li> Excellent written and verbal communication skills. </li> Desired <li> Bachelor or Masters degree in highly quantitative field (computer science, or electrical </li> engineering, mathematics, statistics) or equivalent domain specific experience in lieu of a degree. <li> Proficient in machine learning data workflows, data collection methodologies, and data analysis. </li><li> Experience with architecting, designing, developing software solution in Azure and on-prem </li> environments. <li> Certifications AI / ML and Azure Cloud platforms</li> Benefits This position offers an excellent opportunity for significant career development in a fast-growing and challenging entrepreneurial environment with a high degree of individual responsibility.

At Net2Source, we are seeking a dedicated Technical Business System Analyst II/ Machine Learning Engineer II to join our team in Houston TX. This is a W2 role (no C2C) and offers a hybrid shift experience for a duration of 12 months, with the potential for extension for the right match. Job: Business System Analyst II/ Machine Learning Engineer II Location: Houston, TX Schedule: sun- wed 10am to 8pm , no travel, onsite 4 days a weekDuration: 6 months (likely to be extended out ) – the team is currently doing is only increasing so the hiring manager see’s no reason why they wouldn’t be extended out as long as they are performing in the role. Team/Environment: 24/7 team that provides support to CAT customers. Team has 8 different workstations and the environment is very collaborative. Jason and his team lead will take 2-3 weeks to get the person trained on Caterpillar processes and procedures and trained on their internal tools. They use salesforce for documenting customer updates. Top Skills:<ul><li>Knowledge of engineering principles, internal combustion engine and operational practices, control system logic, driven equipment, and processes</li><li>Working knowledge and mechanical skill set including the use of hand tools, measuring tools.</li><li>Strong analytical experience/background – (they use Power BI and Tableau )</li><li>Ability to collaborate with different teams.</li></ul> Day To Day:<ul><li>Monitor Equipment through Caterpillar Marine Digital Tools</li><li>Review equipment alerts.</li><li>Act on alerts with Technical Lead, CORE Manager, Fleet Manager, and customers.</li><li>Provide comments on actions.</li><li>Cross Reference Digital tools while troubleshooting.</li><li>Provide technical information to Customers, Fleet Managers, and Dealer’s for service with Trouble calls.</li><li>Document issues and status through the Sales Force Platform.</li><li>Communicate noted issues to Customers through the Sales Force Platform.</li></ul> Education & Experience Required:<ul><li>High School Diploma, GED or Equivalent</li><li>1-3+ yrs. working on machinery such as combustion engines, hydraulic systems, or pneumatic devices.</li><li>Or 1-3+ yrs. working with analytical data, utilizing quantitative analysis, preferably in data science, or engineering.</li><li>Will consider internship exp.</li></ul> Interview Process: 1 Round video interview Thanks, And Regards Aditya AgnihotriLead Technical RecruiterNet2Source Inc.270 Davidson Ave, Suite 704, Somerset, NJ 08873Office: (201) 340-8700 x 378 | Cell: (503) 207-6401 | Email Id: agnihotri.aditya@net2source.com

<h3>Job Description</h3><div>Job Description<div><div>PMG is a digital company that helps marketers connect people with their brand. Focused on people and grounded in data, our award-winning culture fosters meaningful careers. Partnering with the most iconic brands in the world, we put people at the center of everything we do to deliver value, innovation, and business transformation.</div>As our Lead Machine Learning Engineer, you will be the pioneering hire in our Creative Insight's ML division, laying the foundation for a team that will grow to include additional ML engineers. You will collaborate closely with our existing team of software engineers to ideate, implement, and integrate ML technologies that analyze ad content performance and optimize audience targeting and modeling. You will be at the forefront of these initiatives, overseeing them from the initial concept stage all the way through to prototyping and implementation, in addition to conducting experiments. You will not throw anything over a wall, nor will you be expected to catch anything thrown. Responsibilities<ul><li><ul><li>Develop and implement machine learning models to predict and analyze the performance of digital advertisements.</li><li>Utilize statistical analysis and ML techniques to understand the correlation between ad content and audience engagement.</li><li>Lead the ideation, design, and execution of data-driven projects that enhance our ability to target audiences more effectively.</li><li>Innovate and implement ML solutions that can scale across various platforms and customer segments.</li><li>Establish metrics and evaluation frameworks to assess the effectiveness of ML models.</li><li>Wear an MLOps hat: monitor and maintain AI/ML Models in production, determining, for example, when to retrain or replace an existing model.</li><li>Leverage Generative AI to (for example) deliver AI-assisted asset generation workflows based on historical asset performance. </li><li>Mentor and lead a growing team of ML engineers, fostering a collaborative and results-driven environment.</li></ul></li></ul>Skills & Experience<ul><li><ul><li>Master's or Ph.D. in Computer Science, Machine Learning, Statistics, or a related field.</li><li>Minimum of 5 years of experience in machine learning, data science, or a similar role, with a proven track record of deploying models in production environments.</li><li>2+ years of experience leading and mentoring engineers</li><li>Strong expertise in programming languages such as Python and ML libraries like TensorFlow, PyTorch, or scikit-learn.</li><li>Experience in advanced predictive modeling, natural language processing, or computer vision.</li><li>Deep understanding of machine learning algorithms, including supervised and unsupervised learning, deep learning, and neural networks (inc. Transformers).</li><li>Familiarity with Generative AI systems.</li><li>Experience with data manipulation and analysis using SQL, pandas, or similar tools.</li><li>Strong analytical skills with the ability to collect, organize, analyze, and disseminate significant amounts of information with attention to detail and accuracy.</li><li>Strong hands-on experience applying Software Engineering principles and practices (e.g. source code control, API design, and design patterns) to machine learning models (and other probabilistic workflows).</li><li>Excellent communication and leadership skills to lead project teams and interface with clients and stakeholders.</li></ul></li></ul>Desirable Attributes<ul><li><ul><li>Prior experience in digital marketing or advertising technology.</li><li>Familiarity with cloud computing services like AWS, Google Cloud, or Azure.</li><li>A deep passion to create a "graph-of-thought" LLM workflow using a DAG (or DAG-like) execution engine.</li></ul></li></ul><div>About PMG: PMG is a global independent digital company that seeks to inspire people and brands that anything is possible. Driven by shared success, PMG uses business strategy and transformation, creative, media, and insights, as well as its proprietary marketing intelligence platform Alli, to deliver Digital Made for Humans™. Our team is made up of over 500 employees globally, and our work for brands like Apple, Best Western Hotels & Resorts, CKE Restaurants, Experian, Intuit, Kohler, Nike, Sephora, Therabody, and Whole Foods runs across 85+ countries and has received top industry recognition from Cannes Lions to Adweek Media Plan of the Year.Named to Ad Age's 2023 A-List, MediaPost's 2023 Independent Agency of the Year, and Adweek's 2021 Breakthrough Media Agency of the Year, PMG has grown through commitments to continuous improvement, business integrity, and cultivating dynamic relationships. We are proud to be named among Fast Company's Best Workplaces for Innovators and Fortune's Best Workplaces in Advertising & Marketing (ranked #1), and to be the only company named to Ad Age's Best Places to Work nine years in a row.Being part of PMG means being part of a company culture that's unmatched in digital. We're willing to work hard to serve our clients and deliver value, results, and innovation -- which often requires true grit and remaining agile. We believe in taking care of ourselves and each other so that we continuously improve in every way. We'd love to get to know you and share more about why we love PMG and the work we do. In alignment with our core values to be inclusive and always change for the better, PMG is committed to creating a more diverse and inclusive culture, and we are proud to be an equal opportunity employer. We believe we only change for the better by bringing different people to our company. PMG recruits, employs, trains, compensates, and promotes regardless of race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status. Learn more about our commitment to Diversity and Inclusion and our action plan for change here.</div></div></div>

Center 1 (19052), United States of America, McLean, VirginiaSenior Machine Learning Engineer (Remote-Eligible)As a Capital One Machine Learning Engineer (MLE), you''ll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You''ll participate in the detailed technical design, development, and implementation of machine learning applications using existing and emerging technology platforms. You''ll focus on machine learning architectural design, develop and review model and application code, and ensure high availability and performance of our machine learning applications. You''ll have the opportunity to continuously learn and apply the latest innovations and best practices in machine learning engineering. What you''ll do in the role: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you''ll be expected to perform many ML engineering activities, including one or more of the following:Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams. Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation).Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment. Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications. Retrain, maintain, and monitor models in production.Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale.Construct optimized data pipelines to feed ML models. Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code. Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI. Use programming languages like Python, Scala, or Java. Capital One is open to hiring a Remote Employee for this opportunityBasic Qualifications:Bachelor''s degree. At least 4 years of experience programming with Python, Scala, or Java (Internship experience does not apply)At least 3 years of experience designing and building data-intensive solutions using distributed computing At least 2 years of on-the-job experience with an industry recognized ML frameworks (scikit-learn, PyTorch, Dask, Spark, or TensorFlow) At least 1 year of experience productionizing, monitoring, and maintaining models Preferred Qualifications:1+ years of experience building, scaling, and optimizing ML systems1+ years of experience with data gathering and preparation for ML models2+ years of experience developing performant, resilient, and maintainable codeExperience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud PlatformMaster''s or doctoral degree in computer science, electrical engineering, mathematics, or a similar field 3+ years of experience with distributed file systems or multi-node database paradigmsContributed to open source ML software Authored/co-authored a paper on a ML technique, model, or proof of concept3+ years of experience building production-ready data pipelines that feed ML models Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance At this time, Capital One will not sponsor a new applicant for employment authorization for this position.No agencies please. Capital One is an Equal Opportunity Employer committed to diversity and inclusion in the workplace. All qualified applicants will receive consideration for employment without regard to sex, race, color, age, national origin, religion, physical and mental disability, genetic information, marital status, sexual orientation, gender identity/assignment, citizenship, pregnancy or maternity, protected veteran status, or any other status prohibited by applicable national, federal, state or local law. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City''s Fair Chance Act; Philadelphia''s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at [Click Here to Email Your Resum]. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.For technical support or questions about Capital One''s recruiting process, please send an email to [Click Here to Email Your Resum]Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site.Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

MACHINE LEARNING ENGINEER (Retail or ecommerce Experience Manadatory) Location: Remote MUST HAVE- Python, Tensorflow, Scala Must Have Experience in machine learning techniques, pipelines and applications Experience with writing robust, idiomatic and easy-to-understand backend code (Python, Java, Scala). Experience writing scalable and performant data pipelines on distributed systems (e.g. Hadoop, Spark) - preference in candidates with experience in Airflow Nice To Have Experience with cloud platforms like GCP or AWS Familiar with ML lifecycle: training, deploying, monitoring, debugging, and iterating on production machine learning systems. Familiar with modern machine learning frameworks such as TensorFlow or Pytorch

Machine Learning Engineer Jobs in Dallas, TX

Machine Learning Engineer
October 19, 2024

Machine Learning Engineer Ii
October 18, 2024

Lead Machine Learning Engineer
October 14, 2024

Senior Machine Learning Engineer Remoteeligible
October 12, 2024

Machine Learning Engineer Ecommerce Or Retails
October 2, 2024

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Machine Learning Engineer Jobs in Dallas, TX

Machine Learning EngineerOctober 19, 2024

Machine Learning Engineer IiOctober 18, 2024

Lead Machine Learning EngineerOctober 14, 2024

Senior Machine Learning Engineer RemoteeligibleOctober 12, 2024

Machine Learning Engineer Ecommerce Or RetailsOctober 2, 2024