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Remote Audio Machine Learning Jobs in Connecticut

This role can be remote in the United States and supports the Motion Drive Products Division in New ... Our Team Dynamics Our teams support each other, collaborate, and never stop learning. Everyone ...

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You will then deploy what your team builds in remote events for the top networks and brands in ... audio path, fiber linked systems, digital video compression and transmission standards, PC ...

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Remote Audio Machine Learning information

What is the difference between Remote Audio Machine Learning vs Remote Audio Engineer?

AspectRemote Audio Machine LearningRemote Audio Engineer
Required CredentialsBackground in machine learning, data science, or AI; often a degree in computer science or related fieldsAudio engineering, sound design, or music production degree or certification
Work EnvironmentPrimarily focused on developing algorithms, data analysis, and model training, often in a tech or research settingRecording, mixing, editing audio, often in studios or remote production setups
Employer & Industry UsageTech companies, research labs, AI startups working on audio recognition or enhancementMusic, film, broadcasting, and media production companies

Remote Audio Machine Learning specialists focus on developing algorithms to process and analyze audio data, while Remote Audio Engineers handle the practical aspects of recording and editing sound. Both roles may collaborate but serve different functions within the audio industry.

How does a Remote Audio Machine Learning role typically collaborate with cross-functional teams, and what communication tools are commonly used?

In a Remote Audio Machine Learning position, collaboration with cross-functional teams such as software engineers, data scientists, and product managers is essential. Regular communication is maintained through tools like Slack, Zoom, and project management platforms such as Jira or Trello. Team members often participate in virtual stand-ups, sprint planning sessions, and code reviews to ensure alignment on project goals and timelines. Effective asynchronous communication and clear documentation are especially important in remote settings to keep everyone informed and foster a productive workflow.

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

To thrive as a Remote Audio Machine Learning Engineer, you need strong foundations in digital signal processing, machine learning algorithms, and programming (often Python), typically supported by a degree in computer science, engineering, or a related field. Familiarity with tools such as TensorFlow, PyTorch, and audio processing libraries (e.g., LibROSA), as well as experience with cloud platforms, is highly valuable. Excellent problem-solving skills, self-motivation, and clear remote communication are essential soft skills for collaborating across distributed teams. These competencies enable the development of robust, innovative audio ML solutions while ensuring effective teamwork and project delivery in a remote setting.

What is a Remote Audio Machine Learning job?

A Remote Audio Machine Learning job involves using machine learning techniques to analyze, process, or generate audio data while working from a remote location. Professionals in this field develop algorithms for tasks such as speech recognition, music classification, noise reduction, or audio synthesis. They often work with large datasets, build and train models, and collaborate with teams online. These roles typically require skills in programming, signal processing, and experience with machine learning frameworks.
What are the most commonly searched types of Audio Machine Learning jobs in Connecticut? The most popular types of Audio Machine Learning jobs in Connecticut are:
What are popular job titles related to Remote Audio Machine Learning jobs in Connecticut? For Remote Audio Machine Learning jobs in Connecticut, the most frequently searched job titles are:
What cities in Connecticut are hiring for Remote Audio Machine Learning jobs? Cities in Connecticut with the most Remote Audio Machine Learning job openings:
GEN AI Sr Data Scientist/Data Scientist

GEN AI Sr Data Scientist/Data Scientist

The Hartford

Hartford, CT • On-site, Remote

$90K - $166K/yr

Full-time

Posted 15 days ago


The Hartford rating

8.8

Company rating: 8.8 out of 10

Based on 104 frontline employees who took The Breakroom Quiz

52nd of 261 rated insurance


Job description

Sr Data Scientist - GD07AEData Scientist - GD08AE

We're determined to make a difference and are proud to be an insurance company that goes well beyond coverages and policies. Working here means having every opportunity to achieve your goals - and to help others accomplish theirs, too. Join our team as we help shape the future.

Senior Data Scientist - AI Horizontal Products

Step into the future with The Hartford as a Senior Data Scientist, where Generative AI is a core strategic capability-it's central to our enterprise strategy. Join a team that's pioneering AIdriven products across underwriting, claims, and customer service, transforming how we operate and make decisions at scale.

As part of our Horizontal AI Products Team, you will investigate emerging models, architectures, and techniques; design rigorous evaluation frameworks; and prototype new products that inform how GenAI is operationalized across the organization. This position is ideal for someone who is intellectually curious, technically deep, and motivated by advancing the state of practice in enterprise Generative AI.

This position offers a Hybrid or Remote work arrangement. Candidates living near one of our locations are expected to work in the office three days per week (Tuesday-Thursday).

Research & Technical Responsibilities

  • Conduct applied research in Generative AI, exploring emerging foundation models, architectures, and inference strategies to address enterprise AI use cases.
  • Lead investigation and experimentation across areas such as:
    • Agentbased and multistep reasoning workflows
    • Retrievalaugmented generation (RAG)
    • Longcontext modeling and information synthesis
    • Prompting strategies and controllability of generative outputs
  • Design and execute rigorous experimental frameworks to evaluate model quality, robustness, latency, cost, and reliability using:
    • Automated metrics
    • Humanintheloop feedback
    • LLMasajudge and comparative evaluation methodologies
  • Create benchmarks and build reproducible pipelines to compare vendor models, opensource alternatives, and internal approaches.
  • Rapidly prototype research ideas using modern GenAI tooling such as:
    • Vertex AI / Google Agent Development Kit
    • LangChain / LangGraph
    • RAG frameworks
    • Hugging Face ecosystems
    • OpenAI APIs
  • Translate research findings into deployable GenAI capabilities, working closely with engineering and MLOps teams to ensure scalability, observability, and responsible AI practices.
  • Contribute to the enterprise GenAI roadmap by identifying gaps, risks, and opportunities informed by ongoing research and industry trends.
  • Partner with stakeholders across Data Science, Technology, and Business teams to align research directions with realworld operational challenges.

Qualifications

  • Masters and 5+ years of industry experience OR PhD and 3+ years of industry experience in machine learning or data science and with 1+ years focused on GenAI.
  • Strong proficiency in Python and modern AI/ML frameworks
  • Demonstrated experience designing experiments, running evaluations, and drawing conclusions from empirical results.
  • Handson experience with Generative AI frameworks and platforms, including Vertex AI, ADK, LangChain/LangGraph, RAG pipelines, Hugging Face, and OpenAI APIs.
  • Deep understanding of:
    • Agent workflows and toolaugmented LLMs
    • Prompt engineering and model controllability
    • Retrievalaugmented generation (RAG) design tradeoffs
    • Generative model evaluation and benchmarking techniques
  • Experience collaborating with engineering and MLOps teams to transition prototypes into production systems.
  • Strong written and verbal communication skills, including the ability to explain research findings, limitations, and tradeoffs to both technical and nontechnical audiences.
  • Authorization to work in the United States without company sponsorship. STEM OPT I983 Training Plan endorsement is not supported for this role.

Compensation

The listed annualized base pay range is primarily based on analysis of similar positions in the external market. Actual base pay could vary and may be above or below the listed range based on factors including but not limited to performance, proficiency and demonstration of competencies required for the role. The base pay is just one component of The Hartford's total compensation package for employees. Other rewards may include short-term or annual bonuses, long-term incentives, and on-the-spot recognition. The annualized base pay range for this role is:

$90,160 - $166,080

The posted salary range reflects our ability to hire at different position titles and levels depending on background and experience.

Equal Opportunity Employer/Sex/Race/Color/Veterans/Disability/Sexual Orientation/Gender Identity or Expression/Religion/Age

About Us|Our Culture | What It's Like to Work Here | Perks & Benefits


What The Hartford employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom


Hartford logo

About Hartford

Sourced by ZipRecruiter

Hartford Financial Services Group, widely recognized as The Hartford, is a renowned company based in Hartford, CT, US. Established in 1810, it has evolved into an industry leader in the insurance and financial services sector, proudly serving more than one million businesses in the US. The Hartford is committed to offering a gamut of insurance products that include homeowners, automobile, and business insurance as well as employee benefits and mutual funds. The company’s core values revolve around customer-focused innovations, diversity and inclusion, and ethical dealings that have earned them a customer-centric reputation. This shapes their mission which revolves around aiding their clients to overcome unforeseen obstacles and enhancing their wealth over time. Among the company's noted accomplishments is being consistently listed among the World's Most Ethical Companies, a testament to their unwavering commitment towards responsible business practices.

Industry

Finance and insurance

Company size

10,000+ Employees

Headquarters location

Hartford, CT, US

Year founded

1810

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