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Summer Machine Learning Software Engineer Jobs in Connecticut

Bespoke Labs

Machine Learning Engineer

Waterbury, CT · On-site

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Bespoke Labs

Machine Learning Engineer

Danbury, CT · On-site

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Bespoke Labs

Machine Learning Engineer

Bridgeport, CT · On-site

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Bespoke Labs

Machine Learning Engineer

New Haven, CT · On-site

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

The Hartford

Senior AI Machine Learning Engineer

Hartford, CT · Hybrid

$123K - $162K/yr

As a Senior Machine Learning Engineer , you will play a critical role in designing, building, and operationalizing productiongrade AI solutions-partnering closely with product, engineering, and ...

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Summer Machine Learning Software Engineer information

What is the difference between Summer Machine Learning Software Engineer vs Summer Data Scientist?

AspectSummer Machine Learning Software EngineerSummer Data Scientist
Required CredentialsBachelor's or Master's in CS, ML, or related fields; coding skills in Python, JavaBachelor's or Master's in Data Science, Statistics, or related fields; strong analytical skills
Work EnvironmentSoftware development teams, coding, model deploymentData analysis, statistical modeling, data visualization
Employer & Industry UsageTech companies, startups, research labsTech firms, finance, healthcare, consulting

While both roles involve working with data and algorithms, Summer Machine Learning Software Engineers focus on developing and deploying machine learning models through coding and software development. Summer Data Scientists primarily analyze data, build statistical models, and generate insights. The roles often overlap but differ in their core activities and skill emphasis.

What are the most commonly searched types of Machine Learning Software Engineer jobs in Connecticut?

The most popular types of Machine Learning Software Engineer jobs in Connecticut are:

Summer Machine Learning Software Engineer jobs near you

Machine Learning Engineer

Bespoke Labs

Waterbury, CT • On-site

Full-time

Re-posted 28 days ago

Job description

About Us

We are AI researchers and builders who understand how to curate data and RL environments that truly improve models. We curated OpenThoughts, one of the best open reasoning datasets, and have trained SOTA models such as Bespoke-MiniCheck and Bespoke-MiniChart.

We are embarked on a journey to build Environments that are entire digital worlds that can be used to push the frontier of agents.

What You'll Be Working On

You will work directly with our research team on RL environment and task creation for agent training. This means designing observation spaces, action spaces, reward signals, and success criteria for new environments — and building the infrastructure that makes world-scale RL training possible. This is a high-ownership role; you will be building novel systems, not maintaining legacy ones.

Must-Have Skills

3+ years of ML engineering experience — model training, fine-tuning, or post-training pipelines in research or production

Strong Python and deep learning proficiency (PyTorch preferred; familiar with training loops, optimizers, mixed precision)

Hands-on experience with LLM post-training — SFT, RLHF, PPO, DPO, or reward model training — and understanding of how training data quality affects model behavior

Familiarity with RL frameworks (Gymnasium, dm_env) and the ability to design or modify reward functions for agent training objectives

Experience running experiments at scale on cloud or HPC (AWS, GCP, SLURM, or Ray)

Solid understanding of evaluation methodology — held-out sets, benchmark design, avoiding train/eval contamination

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