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Audio Machine Learning Intern Jobs in Cambridge, MA

Cellarity

Machine Learning Scientist

Somerville, MA · On-site

... and audio), and perturbation modeling. Scientific Collaboration * Collaborate with ... apply machine learning to diverse disease areas. Cellarity is a product of Flagship Pioneering ...

IBM

IBM Research Intern 2027: AI Systems

Cambridge, MA · On-site

Your role and responsibilities As an intern, you will be responsible for: * Research, design, and ... Demonstrated experience in machine learning, deep learning, large language models (LLMs), AI agents ...

FocusKPI Inc.

Data Science Intern

Boston, MA · Remote

Data Science Intern Statistical Modeling & Marketing Measurement Remote | Internship | Full-time | ... and machine learning models for marketing measurement. This role is designed for someone with ...

FocusKPI Inc.

Data Science Intern

Boston, MA · On-site +1

Data Science Intern Statistical Modeling & Marketing Measurement Remote | Internship | Full-time | ... and machine learning models for marketing measurement. This role is designed for someone with ...

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Showing results 21-40

All JobsAudio Machine Learning Intern JobsAudio Machine Learning Intern Jobs in Cambridge, MA

Audio Machine Learning Intern information

See Cambridge, MA salary details

$27.9K

$46.5K

$96.2K

How much do audio machine learning intern jobs pay per year?

As of Sep 7, 2026, the average yearly pay for audio machine learning intern in Cambridge, MA is $46,543.00, according to ZipRecruiter salary data. Most workers in this role earn between $35,500.00 and $50,300.00 per year, depending on experience, location, and employer.

What does an audio machine learning intern do?

An Audio Machine Learning Intern assists in developing and improving machine learning models that process and analyze audio data. Their tasks may include data preprocessing, feature extraction, model training, and evaluation for applications like speech recognition, sound classification, or music analysis. Interns often collaborate with engineers and researchers to experiment with new algorithms and optimize audio-based AI systems. This role provides hands-on experience in both audio signal processing and machine learning techniques.

What types of projects can an audio machine learning intern expect to work on during their internship?

As an Audio Machine Learning Intern, you can expect to be involved in projects such as developing and fine-tuning audio classification models, working on speech recognition algorithms, or improving the accuracy of sound event detection systems. You may also assist with the collection and preprocessing of audio datasets, as well as support model evaluation and optimization. Collaboration with data scientists, audio engineers, and software developers is common, offering a hands-on learning environment and exposure to end-to-end machine learning workflows in the audio domain.

What are the key skills and qualifications needed to thrive as an audio machine learning intern, and why are they important?

To thrive as an Audio Machine Learning Intern, you need a solid background in signal processing, machine learning fundamentals, and programming skills, often supported by coursework or research in computer science or electrical engineering. Familiarity with Python, TensorFlow or PyTorch, and audio processing libraries like Librosa is typically required. Creativity, problem-solving abilities, and strong collaboration skills help you stand out in this role. These skills are crucial for developing innovative audio solutions, interpreting complex data, and working effectively within research or product teams.

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

AspectAudio Machine Learning InternAudio Data Analyst
Required CredentialsTypically pursuing or recent graduate in Computer Science, Data Science, or related fieldsDegree in Data Analysis, Statistics, or related fields; may have certifications in data tools
Work EnvironmentResearch labs, tech companies, or startups focusing on AI and audio techData-driven departments within media, entertainment, or tech companies
Employer & Industry UsageUsed in AI development, research projects, and product innovationUsed for analyzing audio data, improving user experience, and reporting

The Audio Machine Learning Intern focuses on developing models and algorithms for audio data, often in research or development settings. In contrast, the Audio Data Analyst primarily interprets audio data to generate insights and support decision-making. Both roles require familiarity with audio data, but the intern role emphasizes machine learning skills, while the analyst role centers on data analysis and reporting.

What are popular job titles related to Audio Machine Learning Intern jobs in Cambridge, MA?

For Audio Machine Learning Intern jobs in Cambridge, MA, the most frequently searched job titles are:

What job categories do people searching Audio Machine Learning Intern jobs in Cambridge, MA look for?

The top searched job categories for Audio Machine Learning Intern jobs in Cambridge, MA are:

What cities near Cambridge, MA are hiring for Audio Machine Learning Intern jobs?

Cities near Cambridge, MA with the most Audio Machine Learning Intern job openings:

Audio Machine Learning Intern jobs near you

Machine Learning Scientist

Cellarity

Somerville, MA • On-site

Full-time

Medical, Retirement

Posted 9 days ago

Job description

What if you could join a rapidly growing company and play a critical role in bringing new medicines to patients through looking at and treating disease in a revolutionary way.
What this position is all about:
We seek a Machine Learning Scientist to join our ML team and lead focused efforts in applying and adapting proprietary foundation models to enable Cellarity's predictive drug discovery platform. As a lead ML Scientist the candidate will develop and apply AI methods to identify novel interventions and targets to accelerate early drug discovery.
This role involves hands-on modeling of high-dimensional biological data, leveraging and fine-tuning state-of-the-art foundation models, while enabling interpretability and biological reasoning. Ideal candidate will have demonstrated application of deep learning and computational biology to biological problems.
The successful candidate will work closely with researchers in biology, chemistry, and omics technology in a collaborative environment.
What you would be responsible for:
  • Model Development
    • Apply, fine-tune, and post-train foundation models (e.g., transformer-based, diffusion, VAE architectures) on single-cell RNA-seq data and other modalities to model disease cellular states
    • Build state-of-the-art perturbation models using multi-modal perturbation data (small molecules, CRISPR, cytokines) and phenotypic data, with emphasis on CRISPR screen data (e.g., Perturb-seq).
    • Develop mechanistic interpretability methods to infer gene networks and regulatory mechanisms via attention, graph-based, and/or causal representation methods, supporting downstream applications such as target identification.
    • Deploy and run inference on generative AI models using proprietary datasets on cloud platforms.
    • Establish clinically relevant benchmarking and evaluation frameworks to assess context generalization and guide model improvements.
    • Stay current with the latest research in foundation models, representation learning (across biology, NLP, vision, and audio), and perturbation modeling.

    Scientific Collaboration
    • Collaborate with interdisciplinary scientists from biology, chemistry, and technology teams to translate research questions into cutting-edge ML solutions.
    • Opportunity to collaborate with and co-develop platform modules alongside other Flagship Pioneering companies.
    • Communicate technical concepts clearly to diverse scientific audiences.

What experiences will you need:
  • PhD in Computer Science, Computational Biology, or related field, OR Master's degree with 3+ years or Master's or Bachelor's degree with 6+ years of relevant ML research experience for drug discovery.
  • Strong foundation in statistics, deep learning and generative AI.
  • Experience with high-dimensional biological data analysis (bulk/single-cell RNA-seq, gene regulatory networks, PPI networks, multi-omics integration).
  • Experience with chemical / CRISPR perturbation screen data (e.g., Perturb-seq), including analysis and modeling.
  • Familiarity with single-cell foundation models (e.g., Geneformer, scGPT, scFoundation) and their downstream applications.
  • Experience applying or fine-tuning pretrained foundation models or deep generative models for downstream biological tasks.
  • Experience with cloud computing (AWS/GCP) and MLOps best practices.
  • Excellent communication skills and ability to work in interdisciplinary teams.

What sets you apart:
  • Experience building agentic AI systems (e.g., LLM-based agents, tool use, multi-step reasoning workflows) for scientific discovery or data analysis.
  • Familiarity with target identification and prioritization in drug discovery.

What it's like to work at Cellarity
At Cellarity, we
  • Push Boundaries: We create a legacy with breakthrough science in service of patients.
  • Inject Energy: We build strengths from different perspectives and tell it like it is
  • Own it: We transcend our job descriptions and relentlessly follow through on our commitments.
  • Go all out: We work quickly and with conviction.

Company Summary: Cellarity is a privately held, clinical-phase drug discovery startup using AI and single-cell omics to develop life-changing medicines that are unreachable by traditional methods of drug discovery. Our pipeline spans multiple exploratory programs across different indications, offering broad opportunities to apply machine learning to diverse disease areas. Cellarity is a product of Flagship Pioneering's venture creation engine, which has conceived and created companies such as Moderna (NASDAQ: MRNA), Generate:Biomedicines, and Lila Sciences.
Cellarity is committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status.
Recruitment & Staffing Agencies: Cellarity does not accept unsolicited resumes from any source other than candidates. The submission of unsolicited resumes by recruitment or staffing agencies to Cellarity or its employees is strictly prohibited unless contacted directly by Cellarity's internal Talent Acquisition team. Any resume submitted by an agency in the absence of a signed agreement will automatically become the property of Cellarity, and Cellarity will not owe any referral or other fees with respect thereto.
The salary range for this role is $132,000 - $209,000. Compensation for the role will depend on a number of factors, including a candidate's qualifications, skills, competencies, and experience. Cellarity currently offers healthcare coverage, annual incentive program, retirement benefits and a broad range of other benefits. Compensation and benefits information is based on Cellarity's good faith estimate as of the date of publication and may be modified in the future.
Privacy Notice for Applicants: When you apply for a role at Cellarity, a Flagship Pioneering portfolio company, we collect and use personal information you provide (such as your name, contact details, work history, and application materials) to evaluate your application, communicate with you, and comply with legal obligations. Your application data is processed through Greenhouse, our applicant tracking system, and may also be reviewed using AI-assisted screening tools. We do not sell your personal information. California residents have rights under the CCPA/CPRA including to know, delete, and opt out of the sharing of their personal information. If you are located in the EU or UK, we process your data under GDPR and you have rights to access, rectify, and erase your data. To exercise your rights or for questions, contact privacy@flagshippioneering.com.

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