Machine Learning Engineer (Sound Detection) Job at Sigma Software Group

Staff Applied Machine Learning Engineer - Fraud & Abuse

As a Staff Applied Machine Learning Engineer focused on Fraud & Abuse, you will ...

Location

United States , Bay Area

Salary:

276800.00 - 415200.00 USD / Year

Cash App

Expiration Date

Until further notice

Requirements

12+ years building and operating production software and ML systems for business-critical products
Deep expertise in fraud/risk domains such as payment fraud, identity/account integrity, merchant or marketplace risk, scams, trust & safety, abuse prevention, or compliance decisioning
Strong production ML judgment across feature pipelines, model serving, evaluation, monitoring, low-latency integration, safe rollout, and incident response
Sound judgment around false-positive tradeoffs, noisy labels, adversarial behavior, customer harm, and cross-functional decisions
Experience using AI-assisted engineering tools with appropriate verification, testing, and review for high-stakes systems

Job Responsibility

Build and operate real-time and batch ML decisioning systems for payment fraud, scams, identity and account integrity, merchant and marketplace risk, and abuse prevention
Integrate behavioral, graph, device, network, event-stream, and third-party signals into low-latency model serving, decision APIs, and product controls
Own the production lifecycle for risk decisions, including data contracts, feature quality, online/offline consistency, monitoring, drift detection, safe rollout, rollback, and incident response
Develop feedback loops and verified AI-assisted workflows for triage, investigation support, alert clustering, graph exploration, simulation, and post-incident learning
Partner with modelers, analysts, product, compliance, and operations to balance fraud losses, customer access, false positives, product velocity, support burden, and long-term trust
Create reusable decision and evaluation capabilities that product services, internal tools, and AI-assisted workflows can safely consume

What we offer

Remote work
Medical insurance
Flexible time off
Retirement savings plans
Modern family planning
Other benefits at Block

Fulltime

Machine Learning Researcher Engineer

Machine Learning Engineer / Researcher at BoldVoice, you’ll play a critical role...

Location

United States , New York

Salary:

150000.00 - 220000.00 USD / Year

Helpcare AI

Expiration Date

Until further notice

Requirements

At least 5 years of experience working on machine learning models in production environments, specifically training, fine-tuning, evaluating and directly implementing machine learning models, in the fields of Speech, NLP, and/or Vision
Experience in Automatic Speech Recognition (ASR) will be particularly useful, as will knowledge of phonetics and the ability to discern sounds and accents
Proficiency in Python and frameworks like TensorFlow, PyTorch, or similar
Up to date with latest developments in using LLM tools like Claude Code, Cursor, Codex or similar to rapidly prototype, and ship code quickly

Job Responsibility

Designing, training, and fine-tuning machine learning models for AI coaching, pronunciation feedback, and accent detection. This will include working on LLMs, speech models like Wav2Wec2.0, and multi-modal models like speech to speech models
Deploying these models into production environments for real-time and batch inference
Building reusable and organized data preprocessing pipelines for various data, including audio data, text data and more
Setting up automated evaluation systems to monitor model performance
Optimizing training workflows to reduce time-to-deployment

What we offer

Excellent fully paid health/vision/dental insurance
401K program
Help with relocation to NYC
Access to exclusive startup events, conferences and networks
Generous stock options

Fulltime

Model/Anlys/Valid Officer

Location

United States , Tampa

Salary:

130449.69 - 180218.00 USD / Year

Citi

Expiration Date

August 03, 2026

Requirements

Master’s degree or foreign equivalent in Engineering (any), Data Science, Business Analytics, Mathematics, or related quantitative field
1 year of experience as a Data Analyst, Business Analyst, Banking Analyst, Officer, or related position involving AML and KYC risk and control procedures for banking services
Alternatively, will accept a Bachelor’s degree in the stated fields and 3 years of the specified experience
Fraud detection for money laundering/terrorist financing
Customer risk scoring and transaction monitoring rules and models for AML, KYC
Business Intelligence, Data Visualization for risk assessment, data reporting and KPI dashboards
Exploratory data analysis including empirical data distributions, data reconciliation, missing data imputation, and outlier analysis
Statistical analysis including sampling and supervised and unsupervised machine learning
Analytical programming using SQL,SAS, Python, Spark and Hadoop Ecosystem, VBA in Excel, XML

Job Responsibility

Apply quantitative and qualitative data analysis methods to extract, transform and analyze AML/KYC data using SAS, R programming, Python, and SQL
Perform validation of the bank’s KYC customer risk scoring tools and Anti-Money Laundering (AML) transaction monitoring tools to ensure regulatory compliance and establish risk and controls across multiple regions and lines of business, including Retail, Institutional, Credit Cards, Markets and Private Banking
Develop, enhance and validate quantitative methodologies for measuring and analyzing financial crimes risk – AML/KYC, ensuring the rule-based and machine learning (supervised and unsupervised) techniques are robust and effective
Serve the bank’s lines of defense by providing effective challenge to AML/KYC monitoring tools throughout their lifecycle, ensuring that conceptual soundness, technical specifications, data quality, and performance are validated in accordance with regulatory requirements
Evaluate theoretical construction and implementation of tools, challenging mathematical formulation, variables selection, threshold setting and code using statistical tests, ensuring assumptions and limitations are documented to assess fit-for-purpose
Data preparation and validation for modeling and analysis, handling of missing values and outliers, variable transformations, and feature pre-selection for tool stability
Automate data extraction and data preprocessing tasks, perform ad hoc data analyses, design and maintain complex data manipulation processes using Python
Establish robust controls around data quality, continuous monitoring of data quality flowing into AML tools
checks for completeness, anomalies, drifts, and integrity within core banking and data systems Mantas and EAP/Hadoop
Execute threshold analysis to evaluate and optimize production thresholds for AML monitoring scenarios, exploring data distributions and coverage analysis using SAS, R, Python or SQL to emulate and simulate tool logic

What we offer

medical, dental & vision coverage
401(k)
life, accident, and disability insurance
wellness programs
paid time off packages, including planned time off (vacation), unplanned time off (sick leave), and paid holidays

Fulltime

Digital Software Engineering Senior Group Manager – Head of Quality & Performance Engineering

We are seeking a visionary and experienced Digital Software Engineering Senior G...

Location

India , Chennai; Pune

Salary:

Not provided

Citi

Expiration Date

Until further notice

Requirements

15+ years of relevant experience, with significant time in a product line management, e-commerce, or strategic planning role
Proven track record of managing the full SDLC for large-scale, complex software projects and succeeding in delivering high-quality technology products/services in a high-growth environment where priorities shift rapidly
Extensive experience in designing and implementing CI/CD pipelines and automated testing frameworks
First-class leadership, influencing, and talent management skills, with significant experience managing and developing a Software Engineering Team
Ability to use hard data and metrics to back up assumptions and develop business cases
Deep understanding of various testing methodologies, including performance, functional, and non-functional testing
Strong knowledge of agile development methodologies (Scrum, Kanban) and modern software architecture patterns
Familiarity with AI/ML concepts and their application in software development is highly desirable
Excellent communication and negotiation skills, with experience negotiating internally at a senior level
Bachelor’s/University degree required

Job Responsibility

Lead an AI-first testing strategy to transform quality engineering across applications and platforms
Leverage AI to generate test cases, predict risks, accelerate defect detection, and enable synthetic data generation for comprehensive testing
Implement AI-powered solutions & automation for functional, integration, smoke, and performance testing, as well as self-healing automation
Enable developers to incorporate testing as part of the development lifecycle, including integration and smoke tests within the pipeline
Maximize test coverage and reliability by leveraging AI tools and techniques
Drive the adoption of autonomous, self-healing testing in the code and deployment pipeline to enhance speed, quality, and release confidence
Synthetic test data management
Oversee the end-to-end Software Development Lifecycle (SDLC), implementing best practices for agile development, continuous integration, and continuous delivery (CI/CD)
Design, build, and manage a highly automated testing pipeline that enables rapid, high-quality releases
Champion a "shift-left" approach to quality, embedding testing throughout the development lifecycle

Fulltime

AVP - Fraud Operations Sr Analyst

The Fraud Ops Sr Analyst is a senior level positions responsible for contributin...

Location

Malaysia , Kuala Lumpur

Salary:

Not provided

Citi

Expiration Date

Until further notice

Requirements

4-7 years of relevant experience in fraud risk management, fraud analytics, or digital banking risk within a financial services or regulated environments
Intermediate to senior level experience in a similar position preferred
Strong understanding of digital banking customer journeys and online/mobile fraud typologies
Experience working with commercial digital fraud monitoring platforms or behavioral risk technologies e.g. Threatmetrix, BioCatch etc
Knowledge of Machine learning, behavioral and rule‑based fraud detection approaches
Experience in trend analysis and alerts in early fraud detection
Strong analytical skills with the ability to translate data insights into actionable monitoring recommendations
Effective written and verbal communication skills
Bachelor's degree/University degree or equivalent experience

Job Responsibility

Solve complex fraud prevention and loss control issues with significant cross-departmental and departmental impact
Support fraud detection and monitoring activities across digital access channels, including desktop web, mobile web, and native mobile applications
Monitor and analyze fraud risks associated with digital banking activity, including account takeover, social engineering and scam‑related fraud, suspicious device or session behavior, and unauthorized customer profile or payment‑related changes
Analyze fraud risk across multi‑step digital journeys using behavioral, device, and session‑level indicators rather than isolated transactional events
Develop data‑supported recommendations to improve fraud detection effectiveness and reduce unnecessary customer impact
Conduct post‑implementation analysis to assess strategy performance and control outcomes
Partner with Technology and data teams to support strategy implementation, rule changes, data feed validation, and platform optimization initiatives
Prepare clear and accurate reporting and analytical insights for fraud risk management and governance forums
Highlight material risks, emerging themes, and anomalies through structured analysis and timely escalation
Collaborate with fraud operations, investigations, digital product teams, technology, and data partners to support effective digital fraud risk management

Fulltime

Senior Data Scientist - Digital / Device Intelligence

Socure is seeking a Senior Data Scientist to join our Digital Intelligence team....

Location

United States

Salary:

150000.00 - 185000.00 USD / Year

Socure

Expiration Date

Until further notice

Requirements

Master’s degree (or equivalent practical experience) in Computer Science, Machine Learning, Statistics, or a related quantitative field
6+ years of experience in data science or applied machine learning, including experience working in production environments
Excellent SQL skills and extensive experience with large-scale databases and data modeling
Proven track record of deploying and maintaining ML models in live systems, ideally involving streaming or near-real-time data
Proficiency in Python and distributed computing tools (e.g., Spark, PySpark)
Hands-on experience with ML frameworks such as scikit-learn, XGBoost, TensorFlow, or similar
Excellent communication skills—able to explain complex technical results to non-technical stakeholders and senior leadership
Experience designing and interpreting experiments, working with real-world noisy datasets, and applying sound validation techniques to assess model robustness
Demonstrated ability to break down ambiguous problems, apply analytical rigor, and uncover meaningful insights that influence product or risk strategies
Strong judgment across data quality, model selection, and business impact tradeoffs

Job Responsibility

Design and deploy advanced machine learning systems for device identification, anomaly detection, and fraud prevention—balancing precision, recall, and real-world adversarial dynamics
Contribute to the development of scalable data pipelines and production ML workflows using structured and unstructured telemetry (e.g., browser, mobile, session data)
Investigate high-complexity signals (e.g., emulator use, spoofing, low-entropy fingerprints), applying advanced statistical methods and domain knowledge to detect fraud and abuse
Translate ambiguous business problems into modeling approaches, using a combination of supervised, unsupervised, and heuristic techniques
Partner with engineering, product, and risk teams to contribute to data architecture decisions, signal collection, and planning
Drive experimental design, A/B testing frameworks, and robust validation techniques to ensure model generalizability and long-term trust
Contribute to team standards for ML explainability, risk evaluation, and feature logging
Document methodologies and communicate results effectively through dashboards, presentations, and reports for both technical and executive audiences
Mentor junior data scientists and participate in cross-functional working groups

What we offer

Offers Equity
Offers Bonus
total rewards package includes equity, benefits, and an annual bonus or a commission plan
A collaborative and inclusive work environment that fosters learning and growth
Opportunities to grow into staff-level or technical leadership roles over time

Fulltime

AI Engineer

Reporting to the AI & Technology Oversight Manager, the AI Engineer is responsib...

Location

India , Mumbai

Salary:

Not provided

Waystone Governance Ltd.

Expiration Date

Until further notice

Requirements

Deep understanding of the distinction between Generative AI and Agentic AI, including their foundations, capabilities, and appropriate use cases
Strong understanding of AI, ML and LLM concepts, including prompt engineering, prompt grounding, iterative loop techniques, context windows, embeddings, RAG, agentic workflows
Proven ability to integrate AI capabilities both into low-code automation flows and high-code stacks, including, applications, APIs, microservices, distributed systems, and development or testing tools
Solid software development background with hands-on coding experience in one or more engineering ecosystem such as .NET (C#), Python, or TypeScript
Excellent communication skills, with the ability to translate complex AI concepts for non‑experts and to effectively influence and collaborate with stakeholders at all levels, both technical and non‑technical
Strong writing skills, with the ability to contribute to AI literacy and AI fluency documentation
Strong understanding of responsible AI principles, including governance, bias mitigation, compliance, and risk-based decision-making
Analytical thinking with excellent problem‑solving ability and keen attention to details
Ability to mentor developers and testers, and to drive innovation across engineering, QA, and architecture
Ability to assess AI‑enabled capabilities in third‑party SaaS platforms (e.g., Appian, Salesforce,etc) and provide guidance on responsible, effective adoption

Job Responsibility

Hands-on contributor to the design and development of AI-enabled solutions, capable of writing both production-quality code and rapid experimental prototypes
Develop and implement AI‑enabled microservices, APIs, applications, and internal tools
Integrate AI capabilities following secure, scalable engineering best practices
Design, build and validate AI‑driven solutions leveraging providers such as OpenAI and Anthropic
Enhance low‑code/no‑code automation platforms (e.g., Power Automate, n8n, Workato) by embedding intelligent processing and applying agentic patterns where relevant
Implement Model Context Protocol (MCP) servers for secure AI‑to‑system connectivity
Lead AI‑based document parsing and intelligent data extraction initiatives
Contribute to educating and enabling Enterprise Capabilities areas, including Integration and Automation, by providing guidance, training, and best practices, e.g., on effective use of n8n agents
Engage with business stakeholders to understand requirements, constraints, and key drivers, identifying and implementing high‑value AI opportunities across Waystone
Prototype AI features and iterate towards production‑ready capabilities

Fulltime

AI Engineer

Reporting to the AI & Technology Oversight Manager, the AI Engineer is responsib...

Location

United Kingdom , Leeds

Salary:

Not provided

Waystone Governance Ltd.

Expiration Date

Until further notice

Requirements

Deep understanding of the distinction between Generative AI and Agentic AI, including their foundations, capabilities, and appropriate use cases
Strong understanding of AI, ML and LLM concepts, including prompt engineering, prompt grounding, iterative loop techniques, context windows, embeddings, RAG, agentic workflows
Proven ability to integrate AI capabilities both into low-code automation flows and high-code stacks, including, applications, APIs, microservices, distributed systems, and development or testing tools
Solid software development background with hands-on coding experience in one or more engineering ecosystem such as .NET (C#), Python, or TypeScript
Excellent communication skills, with the ability to translate complex AI concepts for non‑experts and to effectively influence and collaborate with stakeholders at all levels, both technical and non‑technical
Strong writing skills, with the ability to contribute to AI literacy and AI fluency documentation
Strong understanding of responsible AI principles, including governance, bias mitigation, compliance, and risk-based decision-making
Analytical thinking with excellent problem‑solving ability and keen attention to details
Ability to mentor developers and testers, and to drive innovation across engineering, QA, and architecture
Ability to assess AI‑enabled capabilities in third‑party SaaS platforms (e.g., Appian, Salesforce,etc) and provide guidance on responsible, effective adoption

Job Responsibility

Hands-on contributor to the design and development of AI-enabled solutions, capable of writing both production-quality code and rapid experimental prototypes
Develop and implement AI‑enabled microservices, APIs, applications, and internal tools
Integrate AI capabilities following secure, scalable engineering best practices
Design, build and validate AI‑driven solutions leveraging providers such as OpenAI and Anthropic
Enhance low‑code/no‑code automation platforms (e.g., Power Automate, n8n, Workato) by embedding intelligent processing and applying agentic patterns where relevant
Implement Model Context Protocol (MCP) servers for secure AI‑to‑system connectivity
Lead AI‑based document parsing and intelligent data extraction initiatives
Contribute to educating and enabling Enterprise Capabilities areas, including Integration and Automation, by providing guidance, training, and best practices, e.g., on effective use of n8n agents
Engage with business stakeholders to understand requirements, constraints, and key drivers, identifying and implementing high‑value AI opportunities across Waystone
Prototype AI features and iterate towards production‑ready capabilities

Fulltime

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Machine Learning Engineer (Sound Detection)

Job Responsibility

Requirements

What we offer

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