ML Data Scientist
Apple
ML Data Scientist
Job Description
Marcom is the globally led creative team responsible for Apple’s consumer-facing marketing. We ensure the seamless execution of world-class communications across all media and platforms. Every day, hundreds of millions of Apple customers worldwide interact with our products. We drive the strategic and creative work that provides both new and existing customers with simple, engaging, and inspiring marketing experiences. As MP&S DevOps Org, we are committed to continuous learning and delivering solutions on a global scale. By working with a diverse range of multi-functional teams, we are able to combine the best of our expertise to create interactive experiences with a skilled group of software engineers. We thoroughly enjoy the process! You will lead the machine learning project lifecycle, design virtual assistants, and develop advanced analytics to drive innovation and solve business challenges with AIOps expertise. As an ML Engineer, you will oversee the machine learning project lifecycle, employing best practices and optimally managing software delivery. You will lead the design and development of virtual assistants utilizing Conversational AI platforms, fostering innovative concepts for impactful solutions. You will design and develop advanced analytic solutions across diverse functional areas, collaborating with business stakeholders to identify AI/ML challenges and capitalize on LLM technologies. You will provide technical support on LLM and GenAI usage, assist teams in adhering to best practices, and lead AIOps projects, prioritizing clustering, classification, anomaly detection, and capacity prediction. Proficiency in understanding requirements, designing conversational flows, and developing intent and entities for chatbots is crucial.
Locations
- Hyderabad, Telangana, India
Salary
Skills Required
- leading machine learning project lifecycleintermediate
- designing virtual assistantsintermediate
- developing advanced analyticsintermediate
- AIOps expertiseintermediate
- employing best practices in machine learningintermediate
- managing software deliveryintermediate
- designing and developing virtual assistantsintermediate
- utilizing Conversational AI platformsintermediate
- fostering innovative conceptsintermediate
- designing and developing advanced analytic solutionsintermediate
- collaborating with business stakeholdersintermediate
- identifying AI/ML challengesintermediate
- capitalizing on LLM technologiesintermediate
- providing technical support on LLM and GenAIintermediate
- assisting teams in adhering to best practicesintermediate
- leading AIOps projectsintermediate
- clusteringintermediate
- classificationintermediate
- anomaly detectionintermediate
- capacity predictionintermediate
- understanding requirementsintermediate
- designing conversational flowsintermediate
- developing intent and entities for chatbotsintermediate
- proficiency in Conversational AIintermediate
Required Qualifications
- 3+ years of experience implementing AI/ML models in enterprise systems. (experience, 3 years)
- Deep understanding of AI/ML concepts, including supervised and unsupervised learning, deep learning, anomaly detection, and large language models. (experience)
- Expertise in Python and relevant libraries and frameworks (e.g., Pandas, Numpy, TensorFlow). (experience)
- Relevant experience in designing, developing, and deploying conversational bots. (experience)
- Experience working with Prometheus, Splunk, Datadog, and Grafana. (experience)
- Experience in NLP, NLU, ML, and Conversational AI. (experience)
- Expertise in seamlessly integrating bot systems with backend systems, databases, and APIs for smooth data exchange and interactions. (experience)
- Excellent troubleshooting and analytical skills in a complex, distributed environment. (experience)
- Excellent communication, presentation, and collaboration skills. (experience)
- Self-starter, capable of working independently. (experience)
Preferred Qualifications
- BS or MS in Engineering, Computer Science, or a related field. (experience)
Responsibilities
- As an ML Engineer, you will oversee the machine learning project lifecycle, employing best practices and optimally managing software delivery. You will lead the design and development of virtual assistants utilizing Conversational AI platforms, fostering innovative concepts for impactful solutions. You will design and develop advanced analytic solutions across diverse functional areas, collaborating with business stakeholders to identify AI/ML challenges and capitalize on LLM technologies. You will provide technical support on LLM and GenAI usage, assist teams in adhering to best practices, and lead AIOps projects, prioritizing clustering, classification, anomaly detection, and capacity prediction. Proficiency in understanding requirements, designing conversational flows, and developing intent and entities for chatbots is crucial.
- Drive the entire machine learning project lifecycle with best practices and software delivery.
- Lead the design and development of virtual assistants using Conversational AI platforms.
- Engage with business stakeholders and leverage LLM technologies for advanced analytic solutions.
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ML Data Scientist
Apple
ML Data Scientist
Job Description
Marcom is the globally led creative team responsible for Apple’s consumer-facing marketing. We ensure the seamless execution of world-class communications across all media and platforms. Every day, hundreds of millions of Apple customers worldwide interact with our products. We drive the strategic and creative work that provides both new and existing customers with simple, engaging, and inspiring marketing experiences. As MP&S DevOps Org, we are committed to continuous learning and delivering solutions on a global scale. By working with a diverse range of multi-functional teams, we are able to combine the best of our expertise to create interactive experiences with a skilled group of software engineers. We thoroughly enjoy the process! You will lead the machine learning project lifecycle, design virtual assistants, and develop advanced analytics to drive innovation and solve business challenges with AIOps expertise. As an ML Engineer, you will oversee the machine learning project lifecycle, employing best practices and optimally managing software delivery. You will lead the design and development of virtual assistants utilizing Conversational AI platforms, fostering innovative concepts for impactful solutions. You will design and develop advanced analytic solutions across diverse functional areas, collaborating with business stakeholders to identify AI/ML challenges and capitalize on LLM technologies. You will provide technical support on LLM and GenAI usage, assist teams in adhering to best practices, and lead AIOps projects, prioritizing clustering, classification, anomaly detection, and capacity prediction. Proficiency in understanding requirements, designing conversational flows, and developing intent and entities for chatbots is crucial.
Locations
- Hyderabad, Telangana, India
Salary
Skills Required
- leading machine learning project lifecycleintermediate
- designing virtual assistantsintermediate
- developing advanced analyticsintermediate
- AIOps expertiseintermediate
- employing best practices in machine learningintermediate
- managing software deliveryintermediate
- designing and developing virtual assistantsintermediate
- utilizing Conversational AI platformsintermediate
- fostering innovative conceptsintermediate
- designing and developing advanced analytic solutionsintermediate
- collaborating with business stakeholdersintermediate
- identifying AI/ML challengesintermediate
- capitalizing on LLM technologiesintermediate
- providing technical support on LLM and GenAIintermediate
- assisting teams in adhering to best practicesintermediate
- leading AIOps projectsintermediate
- clusteringintermediate
- classificationintermediate
- anomaly detectionintermediate
- capacity predictionintermediate
- understanding requirementsintermediate
- designing conversational flowsintermediate
- developing intent and entities for chatbotsintermediate
- proficiency in Conversational AIintermediate
Required Qualifications
- 3+ years of experience implementing AI/ML models in enterprise systems. (experience, 3 years)
- Deep understanding of AI/ML concepts, including supervised and unsupervised learning, deep learning, anomaly detection, and large language models. (experience)
- Expertise in Python and relevant libraries and frameworks (e.g., Pandas, Numpy, TensorFlow). (experience)
- Relevant experience in designing, developing, and deploying conversational bots. (experience)
- Experience working with Prometheus, Splunk, Datadog, and Grafana. (experience)
- Experience in NLP, NLU, ML, and Conversational AI. (experience)
- Expertise in seamlessly integrating bot systems with backend systems, databases, and APIs for smooth data exchange and interactions. (experience)
- Excellent troubleshooting and analytical skills in a complex, distributed environment. (experience)
- Excellent communication, presentation, and collaboration skills. (experience)
- Self-starter, capable of working independently. (experience)
Preferred Qualifications
- BS or MS in Engineering, Computer Science, or a related field. (experience)
Responsibilities
- As an ML Engineer, you will oversee the machine learning project lifecycle, employing best practices and optimally managing software delivery. You will lead the design and development of virtual assistants utilizing Conversational AI platforms, fostering innovative concepts for impactful solutions. You will design and develop advanced analytic solutions across diverse functional areas, collaborating with business stakeholders to identify AI/ML challenges and capitalize on LLM technologies. You will provide technical support on LLM and GenAI usage, assist teams in adhering to best practices, and lead AIOps projects, prioritizing clustering, classification, anomaly detection, and capacity prediction. Proficiency in understanding requirements, designing conversational flows, and developing intent and entities for chatbots is crucial.
- Drive the entire machine learning project lifecycle with best practices and software delivery.
- Lead the design and development of virtual assistants using Conversational AI platforms.
- Engage with business stakeholders and leverage LLM technologies for advanced analytic solutions.
Tags & Categories
Answer 10 quick questions to check your fit for ML Data Scientist @ Apple.
10 Questions
~2 Minutes
Instant Score
Related Books and Jobs