Own and execute paid acquisition across Meta and TikTok for a DTC brand, managing budgets, optimizing campaigns, and driving creative performance insights.
Compensation
Fee negotiated based on experience and engagement model
Responsibilities
Develop and execute DTC acquisition strategy across Meta and TikTok
Manage campaign structure, budgeting, and optimization decisions
Analyze creative performance at the individual level and design rigorous tests
Allocate and scale spend with discipline against CAC, ROAS, MER, and contribution margin
Launch, optimize, and recover campaigns, diagnosing underperformance
Requirements
Nice to have: $1M+ per month paid media spend under direct control
Manage the valuation of mortgage-backed securities and related financial products.
Compensation
The annual base salary range for this role is $240,000-$260,000 (USD) , which does not include discretionary bonus compensation or our comprehensive benefits package. Actual compensation offered to the successful candidate may vary from posted hiring range based upon geographic location, work experience, education, and/or skill level, among other things.
Responsibilities
Manage the valuation of mortgage-backed securities, including specified pools, CMOs, TBA/TBA options, and non-agency products.
Oversee market data inputs to valuation models, ensuring compliance with the firm’s valuation policy.
Perform model validation for new or upgraded valuation models supporting new products and system enhancements.
Perform price testing analysis against counterparty valuation and third-party pricing vendors such as Bloomberg, JPM PricingDirect, and BofA PriceServe.
Maintain valuation support documentation to evidence the accuracy of investment valuations.
Seeking an NLP engineer for a NLP research team to develop modern NLP solutions including LLMs, agents, RAG, and open-source models fine-tuning and deployment.
Responsibilities
Exploring and combining rich internal and external textual datasets
Building GenAI solutions, leveraging both internal models and external APIs
Formulating research hypothesis to derive alpha
Post-training models for specific tasks
Benchmarking LLM approaches internal tasks
Requirements
Bachelor in computer science or another quantitative discipline
Master’s in computer science or another quantitative discipline
PhD in computer science or another quantitative discipline
Design, evolve, and optimize core trading infrastructure, specifically scaling and enhancing highly scalable, low-latency trading systems for the retail futures trading space.
Compensation
$195,000.00 - $220,000.00 USD annually. In addition, this position will also receive an annual target bonus of up to 15%.
Responsibilities
Design, develop, and optimize Scala-based trading services for high-volume, low-latency, 24x7 environments
Lead architectural strategy for future-state scalability and performance optimization
Mentor and guide junior engineers, promoting best practices and technical excellence
Collaborate cross-functionally with product, engineering, operations, and security teams to translate business requirements into robust and secure technical solutions
Optimize system performance, with focus on JVM tuning for Scala/Akka-based distributed system
RTL Design Engineer to help design and develop next-generation AI accelerator silicon, working across architecture, microarchitecture, and RTL implementation.
Responsibilities
Design and implement high-performance RTL for next-generation AI accelerator silicon, from microarchitecture definition through implementation and integration.
Collaborate with architecture and software teams to translate system-level requirements into efficient hardware microarchitectures.
Drive hardware/software co-design efforts to optimize performance, power, area, and scalability for AI workloads.
Develop and optimize RTL for complex datapaths, control logic, interconnects, and other critical silicon subsystems.
Evaluate architectural and microarchitectural tradeoffs across bandwidth, latency, throughput, and resource utilization.
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