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Audio Speech Machine Learning Jobs in Indiana (NOW HIRING)

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Audio Speech Machine Learning information

What are some common challenges faced when developing machine learning models for audio speech applications?

A key challenge in audio speech machine learning roles is dealing with diverse and noisy audio data, which can significantly affect model accuracy. Additionally, models must be robust to different accents, languages, and speaking styles, requiring large and varied datasets for training and validation. Collaboration with data engineers, linguists, and software developers is often necessary to ensure high-quality data pipelines and model integration into production systems. Staying updated with the latest research and optimizing models for real-time performance are also ongoing aspects of the role.

What is an Audio Speech Machine Learning Engineer?

An Audio Speech Machine Learning Engineer is a specialized professional who designs, develops, and implements machine learning models that process and analyze audio and speech data. Their work involves tasks like speech recognition, speaker identification, and audio event detection by leveraging algorithms and large datasets. These engineers collaborate with data scientists, software developers, and linguists to create applications such as voice assistants, transcription tools, and automated customer service systems. Expertise in signal processing, deep learning frameworks, and programming languages like Python is crucial for this role.

What is the difference between Audio Speech Machine Learning vs Speech Data Analyst?

AspectAudio Speech Machine LearningSpeech Data Analyst
Required CredentialsDegree in Computer Science, Data Science, or related fields; knowledge of ML frameworksDegree in Data Analysis, Statistics, or related fields; experience with data tools
Work EnvironmentResearch labs, tech companies, AI startupsData analysis teams, research institutions, tech firms
Industry UsageDeveloping speech recognition, voice assistants, NLP applicationsAnalyzing speech datasets, improving speech models, reporting insights

Audio Speech Machine Learning focuses on developing algorithms for speech recognition and processing, often involving model training and AI development. Speech Data Analysts interpret speech data, generate insights, and support model improvements. Both roles require strong analytical skills, but their core tasks differ: one builds models, the other analyzes data.

What are the key skills and qualifications needed to thrive as an Audio Speech Machine Learning Engineer, and why are they important?

To thrive as an Audio Speech Machine Learning Engineer, you need a solid background in machine learning, signal processing, and programming (typically Python), along with a relevant degree in computer science or a related field. Familiarity with tools like TensorFlow or PyTorch, audio processing libraries (such as Librosa), and experience with speech datasets and ASR systems are commonly required. Critical soft skills include problem-solving, innovation, and effective communication for collaborating with cross-functional teams. These skills are essential to develop accurate, scalable speech recognition systems that advance voice-driven technology.
What are popular job titles related to Audio Speech Machine Learning jobs in Indiana? For Audio Speech Machine Learning jobs in Indiana, the most frequently searched job titles are:
What job categories do people searching Audio Speech Machine Learning jobs in Indiana look for? The top searched job categories for Audio Speech Machine Learning jobs in Indiana are:
What cities in Indiana are hiring for Audio Speech Machine Learning jobs? Cities in Indiana with the most Audio Speech Machine Learning job openings:

Vision Systems Engineer - Raymond, Ohio (on-site only)

Thomas & Reed, LLC

Carmel, IN

Contractor

Posted 10 days ago


Job description

Vision Systems Engineer
Location: ADC Raymond, OH
Contract to Hire
Duration: 12 month + conversion/extension

Description:

The HDMA Digital Innovation Division, Digital Manufacturing Unit, IoT Solutions Development group was created to survey Honda’s manufacturing business and develop strategy for prioritized development of digital solutions that enable improved production efficiency, quality, and safety for a sustainable future.
The IoT Solutions Engineer is engaging with NA regional plant floor customers to identify opportunities to develop and test technology/concepts and prove the ability to deliver reliable value to our customer. Ideal candidate for this role has a creator mindset, is excited to maintain awareness of digital technology developments, and then develop new, reliable solutions that enable Honda competitiveness, while also being risk averse.

• Development of new digital technology solutions such as vision inspection systems, AI and M/L analysis of machine/sensor data.
• Analyze user/customer needs along with manufacturing problems and align them with product/technology opportunities.
• Contribute to and execution of IoT strategy and roadmap for selected areas.
• Monitor developments of new technologies for IoT potential in future projects
• Support analytical processes, like machine learning in use within proof-of-technology concepts to deployed IoT projects.


QUALIFICATIONS, EXPERIENCE, & SKILLS

Minimum Educational Qualifications: Bachelor’s degree in engineering or engineering-related areas: electrical, controls, systems, computer science, data science or equivalent experience

Minimum Experience: 2+ years’ experience in manufacturing equipment controls, network design, embedded systems, machine learning and/or data engineering with a focus on the automotive industry

Other Job-Specific Skills:
-Understanding, extraction and interpretation of parameter data in a machine that represents the health of the machine components, proper operation, and effects on product quality.
-Knowledge of manufacturing equipment controls and logic – preferably in at least one of Mitsubishi, Rockwell, Siemens, or Omron PLCs.
-Understanding of computer vision algorithms such as segmentation, morphology, pose estimation, camera calibration, image enhancement, feature extraction, classification, 3D Vision and deep learning techniques.
-Experience implementing vision algorithms in C++, Python, HALCON, Matrox, Cognex, and/or Keyence, using traditional rules and/or deep learning.
-Experience with vibration, audio, or current signature analysis

Interested candidates please contact Sue HUettl at shuettl@trllc-cpa.com