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Machine Learning Engineer Biotech Jobs in Connecticut

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

AI Machine Learning Engineer

Hartford, CT ยท Hybrid

$100K - $151K/yr

The Hartford is seeking AI Machine Learning Engineer to build Machine Learning Operations (MLOps) services for the Global Specialty Applied AI team. The Hartford is developing industryleading AI and ...

Senior AI Machine Learning Engineer

Hartford, CT ยท 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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Machine Learning Engineer Biotech information

What does a Machine Learning Engineer do in the biotech industry?

A Machine Learning Engineer in biotech applies advanced algorithms and data analysis techniques to solve biological and medical problems. They work with large datasets such as genomic sequences, medical images, or clinical records to develop predictive models, automate data analysis, and uncover insights that can accelerate drug discovery, diagnostics, and personalized medicine. Their work often involves close collaboration with biologists, data scientists, and software engineers to create tools and solutions that improve healthcare outcomes. Machine Learning Engineers in this field need a strong background in both computational methods and biological sciences.

How do Machine Learning Engineers in biotech typically collaborate with research scientists and domain experts?

Machine Learning Engineers in biotech often work closely with research scientists and domain experts to translate complex biological problems into data-driven solutions. This collaboration involves regular meetings to understand experimental data, refine project goals, and iterate on model development based on domain feedback. Engineers are expected to communicate technical concepts clearly, adapt models to fit scientific needs, and help validate results alongside laboratory teams. This interdisciplinary environment fosters innovation but also requires flexibility and strong communication skills.

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

To thrive as a Machine Learning Engineer in Biotech, you need a solid background in computer science, statistics, and biology, often with an advanced degree in a related field. Experience with programming languages such as Python or R, machine learning frameworks like TensorFlow or PyTorch, and familiarity with bioinformatics tools are typically required. Strong problem-solving, communication, and interdisciplinary collaboration skills set standout candidates apart. These capabilities are crucial for developing effective models that drive scientific innovation and advance biotechnological research.

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

AspectMachine Learning Engineer BiotechData Scientist Biotech
Required CredentialsBachelor's or Master's in Computer Science, Data Science, or related; knowledge of ML frameworksBachelor's or Master's in Data Science, Statistics, or related; strong analytical skills
Work EnvironmentDevelops ML models, coding, deploying algorithms in biotech R&DAnalyzes biological data, interprets results, creates reports
Employer & Industry UsageBiotech firms, pharma companies, research labsBiotech companies, healthcare, research institutions

While both roles work with biological data, Machine Learning Engineers focus on developing and deploying ML algorithms, whereas Data Scientists analyze and interpret biological datasets to inform research and decision-making in biotech settings.

What are popular job titles related to Machine Learning Engineer Biotech jobs in Connecticut? For Machine Learning Engineer Biotech jobs in Connecticut, the most frequently searched job titles are:
What cities in Connecticut are hiring for Machine Learning Engineer Biotech jobs? Cities in Connecticut with the most Machine Learning Engineer Biotech job openings:
Machine Learning Engineer

Machine Learning Engineer

Graham Capital Management, L.P.

Norwalk, CT โ€ข On-site

Full-time

Re-posted 27 days ago


Job description

Job Summary:
Graham Capital Management, L.P. is an alternative investment manager specializing in discretionary and quantitative macro strategies. They are seeking a Machine Learning Engineer to join their Data Science team, where the role involves developing innovative solutions using machine learning and advanced statistical methods to support quant strategies and enhance data insights for stakeholders.
Responsibilities:
โ€ข You will be part of a growing team within Data Science.
โ€ข You will work alongside world-class talent to find innovative solutions to some of the most interesting problems in the buy-side.
โ€ข You will work closely with other areas such as Technology, Quantitative Research and Portfolio Manager groups as well as Risk and Operations to learn about problems they face with respect to data and ultimately develop cutting edge solutions.
โ€ข Your focus will be to dive deep into multiple data sets to understand relationships, develop time series, forecasting models, and support quant strategies, and provide new insights and leverage state-of-the-art machine learning and advanced statistical methods to produce the best data sources for the fund.
Qualifications:
Required:
โ€ข Undergraduate or higher degree in Computer Science, Engineering, Operations Research, or other quantitative discipline
โ€ข 3+ years of hands-on experience with Machine Learning and Statistics on large, unstructured, data sets
โ€ข Experience writing production code for multi-client systems serving model results is a great plus
โ€ข Ability to clearly communicate research findings to technical and nontechnical stakeholders
โ€ข Full-stack experience with Python (preferred) or C++, Spark/Scala, SQL or other distributed data processing technologies as well as experience working comfortably building and deploying services and models in containerized environments
โ€ข Experience with scientific computing, statistics, optimization, time series, panel data, etc.
โ€ข Comfortable handling multiple projects to solve varied problems working with multiple teams
โ€ข Detail-oriented mindset
โ€ข Sense of ownership of his/her work, working well both independently as well as collaboratively
Company:
Who We Are & What We Do: Graham Capital Management, L.P. Founded in 1994, the company is headquartered in Norwalk, USA, with a team of 201-500 employees. The company is currently Growth Stage.