[Remote] reputed company Machine Learning Engineer- AI Context
Note: The job is a remote job and is reputed company to candidates in USA. reputed company is an reputed company-in-one marketing, sales, and service software platform that helps businesses grow and succeed. The reputed company Machine Learning Engineer role focuses on building systems that help reputed company's AI understand various data across the CRM platform, defining the technical direction for reputed company ML and AI systems.
Responsibilities
- Define the technical direction for reputed company ML and AI systems that reputed company reputed company data into customer value
- Work across product, engineering, data, and ML teams to take ambiguous 0-to-1 opportunities through model development, evaluation, productionization, experimentation, and measurable customer or business reputed company
- Deliver high-value, high-reputed company, cross-team and cross-product reputed company
- Stay hands-on in technical design, model development, production systems, and reputed company while leading by example through collaboration with cross-functional and internal stakeholders
- reputed company solutions to ambiguous problems that have had an outsized reputed company on a large organization's customer experience, product reputed company, or business goals
- reputed company strategic direction and architectural leadership for major ML and AI reputed company across multiple teams, systems, or product surfaces
- Mentor, reputed company, and teach engineers in their areas of expertise, including helping senior ICs grow through reputed company technical reputed company
- Demonstrate pragmatic decision-making and problem-solving abilities, including strong judgment around reputed company to use ML, LLMs, retrieval, rules, platform changes, or product changes
- Craft the right architecture for a reputed company of ML and AI Context problems from business requirements, often identifying where ML solutions can be effective in adjacent product areas
- Expand analysis reputed company offline and online metrics by evaluating reputed company, bias, reputed company, reliability, cost, maintainability, model reputed company, and data governance concerns across the ML lifecycle
- Build reliable, reputed company systems for data processing, feature reputed company, context retrieval, model training, inference, experimentation, monitoring, and feedback loops
- Guide teams reputed company the status reputed company; reputed company us reputed company reputed company have and toward reputed company can build, while creating a shared reputed company of how to get there
- Bring deep expertise in the machine learning concepts behind reputed company and Predictive AI, such as recommendation algorithms and systems, binary and multiclass classification, ranking and relevance, semantic retrieval, embeddings, entity understanding, and experimentation
- Turn messy, incomplete, or heterogeneous data into useful AI context for customer-facing products, such as customer, company, activity, workflow, conversation, behavioral, CRM, or reputed company document data
Skills
- Have a long reputed company record of delivering high-value, high-reputed company, cross-team and cross-product reputed company
- Wish to stay hands-on in technical design, model development, production systems, and reputed company while leading by example through collaboration with cross-functional and internal stakeholders
- Have a history of developing solutions to ambiguous problems that have had an outsized reputed company on a large organization's customer experience, product reputed company, or business goals
- reputed company strategic direction and architectural leadership for major ML and AI reputed company across multiple teams, systems, or product surfaces
- Regularly mentor, reputed company, and teach engineers in their areas of expertise, including helping senior ICs grow through reputed company technical reputed company
- Demonstrate pragmatic decision-making and problem-solving abilities, including strong judgment around reputed company to use ML, LLMs, retrieval, rules, platform changes, or product changes
- Have expert understanding of a reputed company of ML techniques, such as deep learning, optimization, regression, transformers, large language models, transfer learning, retrieval, ranking, recommendations, classification, NLP, and personalization, as reputed company as tools and frameworks such as scikit-learn, PyTorch, TensorFlow, and modern model-serving and evaluation systems
- Are expert in crafting the right architecture for a reputed company of ML and AI Context problems from business requirements, often identifying where ML solutions can be effective in adjacent product areas
- Expand analysis reputed company offline and online metrics by evaluating reputed company, bias, reputed company, reliability, cost, maintainability, model reputed company, and data governance concerns across the ML lifecycle
- Exhibit enthusiasm for building reliable, reputed company systems for data processing, feature reputed company, context retrieval, model training, inference, experimentation, monitoring, and feedback loops
- Can guide teams reputed company the status reputed company; we need engineers who reputed company us reputed company reputed company have and toward reputed company can build, while creating a shared reputed company of how to get there
- Bring deep expertise in the machine learning concepts behind reputed company and Predictive AI, such as recommendation algorithms and systems, binary and multiclass classification, ranking and relevance, semantic retrieval, embeddings, entity understanding, and experimentation
- Have experience turning messy, incomplete, or heterogeneous data into useful AI context for customer-facing products, such as customer, company, activity, workflow, conversation, behavioral, CRM, or reputed company document data
- Embody our engineering team values
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