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Machine Learning Engineer Biotech Jobs in Dallas, TX

Job Summary We are seeking a Machine Learning Engineer with strong expertise in machine learning model development, data engineering, and modern cloud-based analytics platforms. This role will focus ...

Sr. Machine Learning Engineer Duration: 12 -24 Months Location: Merrimack, NH/ Smithfield, RI/ Westlake, TX/ Durham, NC/ Covington, KY/ Jersey City, NJ/ Boston, MA Candidate should be local or ...

Lead Machine Learning Engineer

Plano, TX · On-site +1

$98K - $129K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You ...

Machine Learning Engineer We are seeking a Machine Learning Engineer to design and develop robust analytics models using statistical and machine learning algorithms. In this role, you will work ...

Lead Machine Learning Engineer

Plano, TX · On-site +1

$98K - $130K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You ...

Senior Machine Learning Engineer

Plano, TX · On-site

$100K - $137K/yr

Senior Machine Learning Engineer Location: Ann Arbor, Michigan Experience Level: 7+ Years Department: Data Science / Engineering Employment Type: Full-time About the Role: We are looking for an ...

Overview Come join Intuit as a Staff Machine Learning Engineer! In this role, you'll work alongside AI scientists and machine learning engineers to create AI-powered experiences. You'll be expected ...

Come join Intuit as a Staff Machine Learning Engineer! In this role, you'll work alongside AI scientists and machine learning engineers to create AI-powered experiences. You'll be expected to help ...

Senior Machine Learning Engineer

Plano, TX · On-site

$100K - $137K/yr

We turn enterprise data into real-time decisions using advanced machine learning and GenAI. Our team solves hard engineering problems at scale, with real-world industry impact. We're hiring ...

Tiger Analytics is looking for experienced Machine Learning Engineer with Gen AI experience to join our fast-growing advanced analytics consulting firm. Our employees bring deep expertise in Machine ...

Machine Learning Engineer - NJ

Addison, TX · On-site

$54 - $71.50/hr

We are seeking a Machine Learning Engineer to design and develop robust analytics models using statistical and machine learning algorithms. In this role, you will work closely with product and ...

Machine Learning Engineer - NJ

Addison, TX · On-site

$54 - $71.50/hr

We are seeking a Machine Learning Engineer to design and develop robust analytics models using statistical and machine learning algorithms. In this role, you will work closely with product and ...

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Machine Learning Engineer Biotech information

See Dallas, TX salary details

$31.2K

$127.4K

$191.4K

How much do machine learning engineer biotech jobs pay per year?

As of Jun 13, 2026, the average yearly pay for machine learning engineer biotech in Dallas, TX is $127,383.00, according to ZipRecruiter salary data. Most workers in this role earn between $100,400.00 and $153,300.00 per year, depending on experience, location, and employer.

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 the most commonly searched types of Machine Learning Engineer Biotech jobs in Dallas, TX? The most popular types of Machine Learning Engineer Biotech jobs in Dallas, TX are:
What are popular job titles related to Machine Learning Engineer Biotech jobs in Dallas, TX? For Machine Learning Engineer Biotech jobs in Dallas, TX, the most frequently searched job titles are:
What job categories do people searching Machine Learning Engineer Biotech jobs in Dallas, TX look for? The top searched job categories for Machine Learning Engineer Biotech jobs in Dallas, TX are:
What cities near Dallas, TX are hiring for Machine Learning Engineer Biotech jobs? Cities near Dallas, TX with the most Machine Learning Engineer Biotech job openings:
Machine Learning Engineer

Machine Learning Engineer

Compunnel

Plano, TX • On-site

Contractor

Posted 12 days ago


Job description

Job Summary
We are seeking a Machine Learning Engineer with strong expertise in machine learning model development, data engineering, and modern cloud-based analytics platforms. This role will focus on building ML-ready data architectures, developing scalable machine learning solutions, and supporting enterprise analytics initiatives. The ideal candidate will possess hands-on experience with Azure Databricks, Python-based model development, Medallion Architecture, and MLOps practices, along with the ability to collaborate effectively with business and technical stakeholders.
Key Responsibilities
  • Design, develop, and maintain machine learning solutions that support advanced analytics and predictive modeling initiatives.
  • Build and optimize ML-ready data pipelines and data architectures using Medallion Architecture principles.
  • Develop and manage data ingestion, transformation, and curation processes across Bronze, Silver, and Gold data layers.
  • Create scalable feature engineering workflows and production-grade machine learning assets.
  • Design and implement machine learning pipelines using Azure Databricks and related cloud technologies.
  • Leverage Delta Lake, MLflow, and workflow orchestration tools to operationalize machine learning models and data transformations.
  • Develop and maintain Python-based machine learning models, feature engineering processes, and MLOps automation solutions.
  • Build and optimize SQL transformations, views, and ELT pipelines to support analytics and machine learning workloads.
  • Design and maintain feature stores, semantic layers, and curated datasets that support enterprise reporting and machine learning initiatives.
  • Integrate machine learning outputs into analytics platforms, dashboards, and business intelligence solutions.
  • Collaborate with business stakeholders, technical teams, and leadership to translate business requirements into scalable data and machine learning solutions.
  • Establish engineering standards, best practices, and scalable development processes for machine learning and data engineering initiatives.
  • Monitor data quality, model performance, and operational effectiveness of machine learning solutions.

Required Qualifications
  • 5-7 years of hands-on experience in machine learning engineering and data engineering.
  • 10+ years of experience delivering enterprise-scale data, analytics, and machine learning solutions.
  • Strong experience building machine learning models and supporting model development using Python.
  • Extensive experience with Azure Databricks for machine learning, feature engineering, and data engineering workloads.
  • Deep understanding of Medallion Architecture, including Bronze, Silver, and Gold data layer design and implementation.
  • Experience designing ML-ready data architectures and scalable data engineering solutions.
  • Experience migrating workloads to Databricks and implementing modern data platform architectures.
  • Hands-on experience with Delta Lake, MLflow, and Databricks Workflows.
  • Strong proficiency in Python for model development, feature engineering, and MLOps automation.
  • Advanced SQL skills with experience building optimized transformations, views, and ELT pipelines.
  • Experience designing feature stores, semantic models, and machine learning-ready datasets.
  • Strong understanding of machine learning lifecycle management, data engineering best practices, and scalable architecture patterns.
  • Ability to lead technical initiatives and establish engineering standards and development practices.
  • Strong business acumen and ability to communicate effectively with technical and business stakeholders.
  • Experience working in collaborative, fast-paced environments that encourage experimentation and innovation.

Preferred Qualifications
  • Experience working within Microsoft Azure cloud environments.
  • Experience integrating machine learning outputs into analytics platforms and business intelligence solutions.
  • Experience designing dashboards and reporting solutions that surface machine learning insights, data quality metrics, and model performance indicators.
  • Familiarity with Power BI, including DAX, semantic modeling, and visualization best practices.
  • Experience supporting enterprise-scale analytics, data science, and AI initiatives.
  • Experience mentoring technical teams and providing technical leadership on machine learning and data engineering projects.

Compunnel logo

About Compunnel

Sourced by ZipRecruiter

Compunnel is a well-known company located in Plainsboro, NJ, US, recognized in the industry of IT Services and Solutions. Established in 1989, Compunnel offers a suite of services that help businesses integrate technology efficiently into their operations, a recognizable name in the IT solutions sphere for over three decades. The company’s service portfolio includes Digital Transformation, Business Intelligence, Cloud Services, Cybersecurity, and Application Modern Services, among others. Guided by its mission "to innovate with industry-leading digital solutions and disruptive tech strategies for unimagining business growth," the company underlines its commitment to offering out-of-the-box solutions to its clients. Remarkable achievements of the company include serving more than 30 Fortune 500 companies and providing job opportunities for over 50,000 individuals.

Industry

It services

Company size

501 - 1,000 Employees

Headquarters location

Plainsboro, NJ, US

Year founded

1994

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