Lead complex AI/ML initiatives, design, develop, evaluate, and operationalize enterprise AI solutions, mentor junior data scientists, and collaborate across engineering and product teams.
Responsibilities
Design, develop, evaluate, and operationalize complex AI/ML solutions
Apply classification, regression, ranking, forecasting, clustering, and anomaly detection to enterprise AI use cases
Develop and evaluate intent classification, semantic matching, and model-routing techniques
Estimate execution latency, token demand, inference costs, and resource requirements
Bachelor’s degree in Machine Learning, Statistics, Data Science, Physics, Computer Science, or a related field, or equivalent education and industry experience
Lead complex AI/ML initiatives, design, develop, evaluate, and operationalize enterprise AI solutions, mentor junior data scientists, and collaborate across engineering and product teams.
Compensation
The range listed is just one component of BMC's employee compensation package. The annual base salary range represents the low and high end of the BMC salary range for this position. Actual salaries depend on a wide range of factors that are considered in making compensation decisions, including but not limited to skill sets; experience and training, licensure, and certifications; other business and organizational needs. The range listed is zł 251,025 - zł 418,375
Responsibilities
Design and develop AI/ML solutions
Evaluate and operationalize models
Mentor junior data scientists
Collaborate with AI Engineering and Platform Engineering
Lead technical decisions
Requirements
Bachelor’s degree in Machine Learning, Statistics, Data Science, Physics, Computer Science, or a related field
Lead research and development of small and efficient language models, collaborating with cross-functional teams to advance training techniques, optimize architectures, and scale AI solutions.
Machine learning engineer leading the design and build of an agentic AI system to automatically resolve insurance claim denials for healthcare practices.
Compensation
The base pay range for this role is $150,000–$275,000 per year.
Responsibilities
Design and build the architecture for our agentic AI system that autonomously resolves insurance claim denials
Develop specialized AI agents for denial classification, root cause analysis, evidence retrieval, policy reasoning, and appeal generation
Implement multi-agent orchestration frameworks that coordinate complex workflows across research, decision-making, and document generation
Build and optimize RAG systems to retrieve relevant clinical documentation, billing records, and payer policy information
Create evaluation frameworks and feedback loops to continuously improve agent performance and reliability
Requirements
Nice to have: healthcare data experience
Nice to have: understanding of medical billing workflows
Lead Data Scientist (GenAI) to design and deliver enterprise‐scale AI solutions using LLMs, RAG, and MCP. The role partners with business and technical leaders to build secure, scalable, high‐value GenAI capabilities across the organization.
Responsibilities
Lead GenAI architecture and design scalable solutions for enterprise use cases
Build modular LLM pipelines using LangChain, LlamaIndex, and similar frameworks
Define prompting, agent, and RAG strategies that can be reused across teams
Manage the full lifecycle of GenAI projects from development through deployment and MLOps
Ensure responsible AI including governance, compliance, and explainability
Requirements
Bachelor's degree in computer science, data science, ML, NLP, AI, linguistics, or related field
Apply AI engineering expertise to deploy, optimize, and scale models for strategic customers, leading technical journeys from POCs to production endpoints.
Responsibilities
Scope workloads, define metrics (TTFT, throughput, cost/token), build benchmarks, and lead technical POCs.
Serve as the technical lead for customer engineering teams through architecture reviews and rollout planning.
Tune engines (KV cache, speculative decoding, parallelism, quantization) to hit aggressive performance targets.
Profile and diagnose bottlenecks at the engine level to deliver production fixes.
Own end-to-end customer onboarding, deployment, autoscaling, capacity planning, and SLO monitoring.
Define how Unity understands and moderates content flowing through its ad network, building multimodal representation strategies and infrastructure to support safety and relevance at scale.
Compensation
Base Salary Range: ¥831,400 - ¥1,247,000 CNY gross
This range reflects the anticipated base salary for this position. Beyond base salary, this role may be eligible for equity awards and participation in our company incentive plans (such as annual discretionary bonuses or sales commissions).
Responsibilities
Define multimodal content representation strategy across video, image, playable, audio, and text
Partner with product, engineering, and science teams to translate regulatory and contractual obligations into measurable objectives
Define evaluation and labeling infrastructure for scarce, noisy, and contested labels
Build shared foundations such as content embeddings, game level features, evaluation harnesses, and labeling pipelines
Lead architectural direction across teams, raise design and review bar, and mentor senior and mid-level engineers
Requirements
Nice to have: regulatory and policy regimes affecting advertising content
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