Model Compression

Model Compression Engineer Jobs

2 jobs found

Today

Multimodal AI Engineer (Robotics & Foundation Models)

Asiacruit BPO, Inc. United States

United States

Today

Full time Artificial Intelligence Computer Vision Model Deployment Engineering

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Job Description

Multimodal AI Engineer role focused on developing Vision-Language-Action (VLA) foundation models for autonomous robotic systems in a hybrid United States setting.

Responsibilities

Develop, fine-tune, and adapt Vision Transformers (ViTs) and multimodal foundation models for robotic perception and action generation.
Implement action-chunking architectures, including Action Chunking with Transformers (ACT) and Diffusion Policy, to support long-horizon robotic task planning.
Build multi-camera fusion pipelines to combine visual inputs into coherent representations for VLA perception and decision-making.
Create and optimize multimodal feature extraction pipelines that connect visual perception to downstream robotic planning and action-generation systems.
Integrate computer vision workflows, including face recognition and perimeter threat assessment, into multimodal AI pipelines.
Apply parameter-efficient fine-tuning (PEFT) approaches, including LoRA, to adapt foundation models for specific robotic applications.
Use Transformer architectures, visual embeddings, and vector search techniques to improve multimodal representation and information retrieval.
Profile and optimize multimodal models using pruning and other model compression techniques to improve inference efficiency.
Prepare and optimize model weights for deployment using NVIDIA TensorRT and related inference optimization tools.
Evaluate performance through systematic experiments, benchmarking, and iterative improvements.
Collaborate with researchers and engineering teams across VLA, robotics controls, and edge AI to support end-to-end system development.

Requirements

Master’s degree or Ph.D. in Computer Science, Artificial Intelligence, Robotics, Machine Learning, Computer Vision, or related fields.
Approximately 3–5 years of relevant experience across multimodal AI, deep learning, computer vision, foundation models, or robotic learning.
Strong programming skills in Python with hands-on experience using PyTorch.
Experience developing, training, or fine-tuning Transformer-based, Vision Transformer, or multimodal deep learning models.
Understanding of vision-language models, multimodal representation learning, and integrating visual inputs into decision-making systems.
Practical experience with PEFT, including LoRA or similar techniques.
Familiarity with robotic learning and action-generation approaches such as ACT, Diffusion Policy, imitation learning, or reinforcement learning.
Experience with multi-camera perception, visual feature fusion, or similar computer vision pipelines.
Knowledge of model profiling and optimization methods such as pruning and quantization.
Familiarity with NVIDIA DeepStream, TensorRT, or GPU-accelerated inference is an advantage.
Knowledge of embeddings and vector search, plus multimodal data processing, is a plus.
Strong analytical and problem-solving skills, with the ability to run experiments and translate research results into engineering solutions.
Ability to work hybrid and be available for on-site work at a designated research location if required for future projects.

Technologies

Python, PyTorch
Vision Transformers (ViTs)
Transformer architectures
Action Chunking with Transformers (ACT)
Diffusion Policy
LoRA, Parameter-efficient fine-tuning (PEFT)
Vector search
Pruning, model compression
NVIDIA TensorRT, NVIDIA DeepStream
GPU-accelerated inference
Imitation learning, reinforcement learning

Why Join

Work on emerging technologies at the intersection of multimodal AI, foundation models, and robotics.
Develop AI systems that connect visual perception, planning, and physical execution.
Explore advanced approaches to VLA model adaptation, action generation, and multimodal learning.
Contribute to real-world AI applications involving autonomous systems and intelligent perception.
Collaborate with researchers and engineers on challenging AI research and development projects.

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2mo ago

Audio AI Engineer

Dev Technology Reston, VA

Reston, VA

2mo ago Closed

$80k - $160k/yr Full time Ai Engineer Artificial Intelligence Asr

This position is no longer accepting applications (closed Sep 9, 2026).

Job Description

Dev Technology is building a multilingual audio foundation to power a mobile translation experience that runs performantly on an iPhone. In this onsite role in Reston, VA, you will develop and improve a speech-to-text core, with ownership spanning multilingual ASR data, model adaptation for constrained devices, and reproducible evaluation of real-world quality.

What you’ll do

Ingest, clean, segment, label, and version multilingual audio and transcript datasets, with specific attention to code-switching and borrowed-word behavior across the target language set.
Fine-tune and compress large ASR models to meet iPhone-class memory, latency, and battery constraints while preserving transcription quality, using approaches such as LoRA/QLoRA, quantization, distillation, or other parameter-efficient and size-reduction techniques as needed.
Create model packaging that supports selecting and downloading language-specific weights on demand based on operator context (for example, pulling only Chinese ASR weights for a Chinese-speaking interview).
Build model behavior and evaluation around when to transcribe a borrowed English term as-is versus rendering it via transliteration or a native equivalent in the source language.
Develop reproducible evaluation pipelines that measure word/character error rate, latency, and robustness to factors including accent, noise, speaking rate, and code-switching, and report results against defined success criteria per language and deployment target.
Write clear model cards, dataset documentation, and evaluation write-ups so both technical and non-technical stakeholders can understand model purpose, comparisons, and known risks and limitations.

Requirements

Bachelor’s degree in Computer Science, Data Science, Machine Learning, Computational Linguistics, or a closely related field.
Strong data-engineering experience building production pipelines for large, messy, or unstructured audio and text datasets.
Hands-on experience fine-tuning or adapting speech/audio models using parameter-efficient methods (LoRA, QLoRA, adapters) and/or compression techniques (quantization, distillation, pruning) for constrained hardware.
Practical experience developing and evaluating ASR/speech-to-text models across multiple languages, including error analysis under real-world conditions such as accents, noise, and code-switching.
Strong Python and SQL skills, with experience using tools such as PyTorch, Hugging Face Transformers/PEFT, torchaudio, and librosa.
Experience deploying and monitoring production ML systems, including secure handling of sensitive audio, transcripts, and derived data in a regulated environment.
Ability to explain model behavior, tradeoffs, and limitations to both technical and non-technical stakeholders.

Technologies

Python, SQL, PyTorch
Hugging Face Transformers, PEFT
torchaudio, librosa
LoRA, QLoRA, quantization, distillation, pruning
iPhone, iOS, Swift, AVFoundation

Role scope

This position owns the speech-to-text model: its data, training/adaptation, on-device size and latency, and transcription accuracy across languages.
It does not own iOS application development, translation (source-language-to-target-language), or the Swift/AVFoundation integration layer; those are handled by a separate mobile engineering function, with close collaboration.

Salary and location

USD 80,000 - 160,000 per yearly

Reston, VA (onsite)

Benefits

Generous and flexible time-off policy
Flexible work schedules and telework options, including remote work availability for eligible projects
Career development opportunities: mentorship program, Dev University technical and management training, hands-on learning through DevLab, tuition reimbursement, and paid training opportunities
Industry-leading benefits including a choice of two health plans with dental and vision, flexible spending account, commuter benefits, life insurance, and more
401K matching with a 5% matching contribution
Regular team and company social events including an annual party, happy hours, fitness challenges, and more
Community engagement support, including employer match for donations and time off for volunteer efforts

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Model Compression Engineer Jobs

Multimodal AI Engineer (Robotics & Foundation Models)

Audio AI Engineer

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