Senior ML Engineer (Audio) Job at Uber (Hyderabad)

Senior Speech & Audio Biomarkers ML Engineer / Data Scientist / LLM Researcher

Adalyon is transforming clinical trials with a behavioural-intelligence platform...

Location

Finland

Salary:

Not provided

Life Science Talent

Expiration Date

Until further notice

Requirements

Advanced degree PhD, postdoctoral experience, or equivalent research depth in speech technology, audio signal processing, acoustics, machine learning, data science, computational linguistics, or a related field
Audio and NLP experience – You have built systems that process raw audio and transcripts to derive actionable insights. Familiarity with prosodic and spectral features, and the ability to engineer features like jitter, shimmer and harmonic-to-noise ratio, which have been shown to correlate with cognitive and emotional conditions
Speech processing toolkits: Experience with speech processing toolkits (e.g., librosa, Kaldi, Praat) and ML frameworks (PyTorch, TensorFlow, scikit-learn) is essential
LLM expertise – Hands-on experience with large language models, including prompting, fine-tuning and integrating them into downstream ML pipelines. Ability to interpret and control LLM outputs to ensure transparency and reproducibility, avoiding the unpredictable behaviour of generic LLMs
Startup mindset – Comfortable working in an agile, evolving environment. You take initiative, think creatively and can operate with limited structure. You thrive when delivering an MVP while planning for scalable solutions
Practical programming ability, ideally in Python and relevant scientific/data tooling. You do not need to be a software engineer, but you must be able to build the systems and pipelines needed for your research.

Job Responsibility

Conversational design & data pipeline
Signal processing & feature extraction
Model development & integration
Validation & evidence generation
Research & innovation

What we offer

A competitive salary package that reflects your experience and the value you create
The opportunity to work with advanced AI, acoustic analysis, and speech-based biomarker technology at an early stage
A central and highly influential role with direct access to research and technology leadership
High autonomy, high visibility, and the opportunity to shape the scientific foundation of a growing company
A dynamic and flexible startup environment with room for deep technical discussion, scientific exploration, and practical impact

Fulltime

Senior Inference ML Runtime Engineer

The Inference ML Engineering team at Cerebras Systems is dedicated to enabling o...

Location

United States; Canada , Sunnyvale; Toronto

Salary:

Not provided

Cerebras Systems

Expiration Date

Until further notice

Requirements

Bachelor’s, Master’s, or PhD in Computer Science, Computer Engineering, Mathematics, or a related field
8+ years of experience in large-scale software engineering, with a focus on deep learning or related domains
Proficiency in Python for building and maintaining scalable systems
Advanced proficiency in C++, with an emphasis on multi-threaded programming, performance optimization, and system-level development
Demonstrated experience driving cross-functional projects
Experience building and scaling large-scale inference systems for LLMs or multimodal models
Familiarity with LLM serving frameworks, such as vLLM, SGLang, and TensorRT-LLM
Solid understanding of software architectural patterns for large-scale, high-performance applications
Hands-on experience with ML frameworks, such as PyTorch, and a strong understanding of their underlying architectures
Strong problem-solving skills, with the ability to balance technical depth with practical implementation constraints

Job Responsibility

Drive and provide technical guidance to a team of software engineers working on complex machine learning integration projects
Design and implement ML features (e.g., structured outputs, biased sampling, predicted outputs) that improve performance of generative AI models at inference time
Design and implement high-throughput, low-latency multimodal inference models that support delivery of image, audio, and video inputs and outputs
Maintain our scalable serving backend for handling many concurrent requests per minute
Scale our inference service by implementing detailed observability throughout the entire stack
Analyze and improve latency, throughput, memory usage, and compute efficiency on the service and the implementation of various features
Optimize software to accelerate generative LLM inference by achieving high throughput and low latency
Stay up-to-date with advancements in machine learning and deep learning, and apply state-of-the-art techniques to enhance our solutions
Evaluate trade-offs between different approaches, clearly articulate design choices, and develop detailed proposals for implementing new features
Uncover, scope, and prioritize significant areas of technical debt across the software stack to ensure continued high quality of the inference service

What we offer

Build a breakthrough AI platform beyond the constraints of the GPU
Publish and open source their cutting-edge AI research
Work on one of the fastest AI supercomputers in the world
Enjoy job stability with startup vitality
Our simple, non-corporate work culture that respects individual beliefs

Senior MLOps Engineer - Data Ingestion - Paris

We are looking for a Senior MLOps Engineer to join the Panda Team (Data & ML Ope...

Location

France , Paris

Salary:

Not provided

Doctolib

Expiration Date

Until further notice

Requirements

You have at least 7+ years as an MLOps Engineer or ML Platform Engineer with proven production model lifecycle management experience
You have expert-level experience with ML orchestration tools (MLflow, Braintrust, or similar) for batch processing and inference pipelines
You have a strong Site Reliability Engineering (SRE) foundation with focus on operations excellence, reliability, and observability
You have expertise in Python for automation and ML pipeline scripting
You have strong proficiency with infrastructure-as-code tools such as Terraform and container orchestration (Kubernetes)
You have experience with model evaluation frameworks and golden dataset management
You have a solid understanding of cloud infrastructure (preferably GCP, AWS, or Azure)
You have excellent problem-solving skills with focus on identifying and resolving infrastructure bottlenecks
You are fluent in English

Job Responsibility

Design and implement end-to-end ML model pipelines in production (LLM and custom models) with robust deployment, evaluation, and monitoring frameworks
Own data pseudo-anonymization architecture within ingestion services, converting Tier 0 (personal identifiers) to Tier 1 (anonymized data) while ensuring data quality and model performance
Build and maintain secure data export services with ML-based threat detection to prevent attack vectors (SQL injection, etc.) using adaptive models rather than manual rules
Manage golden datasets and implement production model evaluation frameworks to ensure anonymization quality and system reliability
Build and maintain data pipelines that efficiently extract, transform, and load data from various sources, handling multiple data formats (text, images, audio, video)
Implement automation and orchestration tools using ML orchestration platforms (MLflow, Braintrust, or similar) to streamline infrastructure provisioning and reduce manual effort
Monitor data and ML platforms for performance, reliability, and security
identify and troubleshoot issues proactively
Mentor team members on MLOps expertise and best practices to reduce knowledge silos and build organizational capability

What we offer

Free comprehensive health insurance for you and your children
25 days of paid vacation per year, plus up to 14 days of RTT
Free mental health and coaching services through our partner Moka.care
Work from abroad for up to 10 days per year thanks to our flexibility days policy
Lunch vouchers (Swile card) worth €8.50 per working day, with €4.50 covered by Doctolib
A subsidy from the work council to refund part of the membership to a sport club or a creative class
50% reimbursement of your public transport subscription
Parent Care Program: receive one additional month of leave on top of the legal parental leave
For caregivers and workers with disabilities, a package including an adaptation of the remote policy, extra days off for medical reasons, and psychological support
Relocation support in case of international mobility

Fulltime

Senior Software Engineer

As a Senior Software Engineer in Desktop Applications, you’ll play a key role in...

Location

Australia , Sydney

Salary:

Not provided

Heidi

Expiration Date

Until further notice

Requirements

5+ years of professional software engineering experience, with clear ownership of complex systems or products
Strong experience with systems-level programming (Rust preferred
C++ or Go acceptable), including performance, memory management, and concurrency
Hands-on experience building or maintaining desktop applications (Tauri, Electron, or native), with an understanding of OS-level concerns such as file systems, permissions, packaging, and updates
Experience with modern frontend technologies such as React / Next.js, and comfort working across the frontend–backend boundary
Comfortable owning ambiguous, high-impact technical problems and driving them to resolution with a high degree of autonomy
Strong product intuition and a user-centric mindset, particularly for tools used daily by professionals in high-stakes environments
Demonstrated ability to embrace AI as a force multiplier in software engineering—using it thoughtfully for system design, problem-solving, debugging, testing, and improving overall development velocity

Job Responsibility

Lead the development of Heidi’s cross-platform desktop applications using Tauri, Rust, and Next.js, shipping production-grade software on macOS and Windows (Linux a plus)
Own the end-to-end desktop experience, from system architecture and native integrations to frontend implementation, performance, and long-term maintainability
Design and build high-performance Rust components powering real-time audio capture, transcription pipelines, local state management, and secure system interactions
Build reliable, well-designed interfaces between Rust backends and web-based frontends, with a strong focus on safety, correctness, and developer experience
Improve the reliability and accuracy of core experiences such as real-time transcription, AI-assisted note generation, offline/online sync, and integrations with healthcare systems
Design and implement end-to-end (E2E) and integration testing strategies for desktop apps, covering Rust services, frontend interactions, and cross-process communication
Actively leverage AI-assisted development workflows to accelerate design, implementation, debugging, and testing across the desktop stack
Advocate for excellent engineering practices, performance, reliability, and accessibility in desktop applications
Collaborate across product, design, ML, and backend teams to deliver features that have a real impact on how healthcare is delivered
Contribute to improving Heidi’s desktop engineering ecosystem and culture as the team continues to grow

What we offer

Flexible hybrid working environment, with 3 days in the office
A generous personal development budget of $500 per annum
Learn from some of the best engineers and creatives, joining a diverse team
Become an owner, with shares (equity) in the company, if Heidi wins, we all win
The rare chance to create a global impact as you immerse yourself in one of Australia’s leading health-tech startups
If you have an impact quickly, the opportunity to fast track your startup career

Fulltime

Senior Firmware Engineer

Cairns Health is building an AI-powered care companion that seniors interact wit...

Location

United States , Sunnyvale

Salary:

170000.00 - 180000.00 USD / Year

Helpcare AI

Expiration Date

Until further notice

Requirements

Strong proficiency in C++ with experience building production, real-time systems
Hands-on experience with audio signal processing for speech, such as: Audio buffering and streaming, Noise estimation / suppression, Voice activity detection or interruption handling
Experience developing on embedded Linux (Yocto preferred)
Solid understanding of multi-threaded, low-latency systems
Comfortable working close to the OS and audio stack

Job Responsibility

Design and implement real-time streaming of speech audio to and from the OpenAI Realtime API
Build and tune audio buffering, latency management, and synchronization for conversational speech
Implement speech interruption detection (barge-in) to support natural, turn-based dialogue
Develop dynamic noise floor detection and related signal conditioning for in-home environments
Apply practical audio signal processing and ML techniques to improve speech quality and robustness
Evaluate and potentially re-architect our Linux audio stack (e.g., PulseAudio → PipeWire)
Optimize performance, memory usage, and reliability on constrained embedded devices
Collaborate closely with firmware, ML, and hardware teams to ship production-quality systems

Fulltime

Senior Software Engineer – AI

NStarX is seeking a highly skilled Senior Software Engineer – AI with a strong f...

Location

India , Hyderabad

Salary:

Not provided

NStarX

Expiration Date

Until further notice

Requirements

Bachelor’s or Master’s degree in Computer Science, Machine Learning, Data Science, or a related field (PhD is a plus)
9+ years of experience in AI/ML engineering or related roles
3+ years of experience in Generative AI with team leadership responsibilities
Proven track record of production-grade ML and GenAI model development and deployment
Programming: Python (preferred)
GenAI Frameworks: Hugging Face Transformers, Diffusers, LangChain, TGI
Serving & Inference: FastAPI, gRPC, NVIDIA Triton, TorchServe
Cloud Platforms: AWS (SageMaker, EKS), GCP (Vertex AI, GKE), Azure (Azure ML, AKS)
MLOps & DevOps: Kubeflow, MLflow, GitHub Actions, Jenkins, Helm, Terraform
Optimization Techniques: Model quantization, distillation, pipeline and tensor parallelism

Job Responsibility

Design, develop, and deploy machine learning models and AI algorithms to address complex business challenges
Lead and mentor a team of AI/ML engineers, ensuring quality and scalability in solution design and implementation
Collaborate closely with cross-functional teams including data scientists, software engineers, product managers, and UX designers
Lead the development and deployment of Generative AI applications across text, code, image, and audio modalities using state-of-the-art LLMs
Design and implement CI/CD pipelines for the GenAI model lifecycle including training, validation, packaging, and deployment
Apply best practices for model performance tuning, cost optimization, and scalable deployment in cloud and hybrid environments
Develop prompt engineering, fine-tuning strategies (LoRA, QLoRA, PEFT), and evaluation protocols tailored to business use cases
Stay current with emerging trends in AI, ML, and Generative AI and drive adoption across teams
Document processes, model architectures, and deployment strategies for traceability and knowledge sharing
Work closely with cross-functional teams to gather requirements and deliver high-quality solutions

What we offer

Competitive salary aligned with market standards
Opportunities for professional development and skill enhancement
A collaborative and innovative work environment

Fulltime

Senior Machine Learning Engineer, Speech Recognition (ASR)

We are on a mission to ensure everyone has access to medical expertise, no matte...

Location

Denmark , København

Salary:

Not provided

Life Science Talent

Expiration Date

Until further notice

Requirements

Strong programming skills in Python and the ability to contribute to production-grade codebases
Hands-on experience in speech recognition and ASR
Experience building ML systems that can be deployed and operated, including pipelines, CI and CD practices, and monitoring
Clear communication and collaboration skills across research, engineering, and product
A Master’s degree in computer science, engineering, mathematics, statistics, physics, or a related field, or equivalent professional experience

Job Responsibility

Train and fine-tune ASR models at scale, including dataset strategy, augmentation, and domain adaptation to real-world clinical audio
Build and improve validation and evaluation frameworks, including WER and targeted analysis across speakers, environments, devices, and clinical terminology
Deploy and operate ASR inference services with focus on reliability, latency, and efficiency in production
Optimize inference latency and throughput, including batching strategies, model export choices, and hardware-aware profiling
Build and maintain APIs and services in frameworks like FastAPI, Kafka, and NVIDIA Triton, and deploy and run them on Kubernetes
Take technical ownership of core ASR components, shaping best practices for modelling, evaluation, and production reliability across the team supporting the growth of engineers working on speech systems
Work closely with product and platform teams on safe rollouts, monitoring, and continuous improvement based on real-world feedback

What we offer

Equipment provided by Corti

Fulltime

Senior Applied AI Engineer

Build production-grade, multimodal (audio/video/text) systems that convert broad...

Location

United States , New York

Salary:

180000.00 - 240000.00 USD / Year

Genius Sports

Expiration Date

Until further notice

Requirements

5–8+ years of professional software engineering experience (backend and/or ML systems)
Strong proficiency in one or more of: Python, Java, Rust
Hands-on experience building production services involving LLM or multimodal model integration (including Gemini, ChatGPT or Claude)
Comfortable with ambiguity, iterative experimentation, and evidence-based decision-making in an Agile environment
Experience with streaming data platforms like Kafka, Pulsar, Flink
Experience with AWS Bedrock or Google Vertex AI
Familiarity with version control systems (e.g., Git)
Excellent problem-solving skills and attention to detail
Ability to work independently and as part of a team
Strong communication skills

Job Responsibility

Build and maintain multimodal agents: Audio sensor agents (acoustic events, sentiment, alignment), Visual sensor agents (scorebug/overlay reading, basic visual cues when applicable), Specialist and decision logic components (structured event outputs, confidence, traceability)
Implement streaming-friendly pipelines: chunking, normalization, time-sync, async execution, and robust retry/backoff for model/tool calls
Develop prompt-as-code with strict JSON contracts, schema validation, and deterministic post-processing to reduce brittleness
Improve system robustness under noisy inputs by: Designing fallback behaviors (degraded modes), Adding guardrails and confidence thresholds, Instrumenting traces/metrics for latency + cost + accuracy
Partner with product, platform, and domain leads to translate sport rules/edge cases into validation logic and to integrate outputs into downstream consumers (tagging, live feeds, analytics)
Contribute to the evaluation workflow by adding test cases, failure mode categories, and regression checks for prompts and model routing
Stay up-to-date with emerging Gen AI technologies, tools, and best practices
Mentor and support other team members in data engineering principles and practices

What we offer

Eligible to take part in Genius Sports Group's benefits plan
Competitive salary and range of benefits
Committed to supporting employee wellbeing and helping you grow your skills, experience and career
Inclusive working environment

Fulltime

Select Country

Senior ML Engineer (Audio)

Job Description

Job Responsibility

Requirements

What we offer

Looking for more opportunities?