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Machine Learning Engineer Biotech Jobs in Dallas, TX

Overview Quarterhill is seeking a Machine Learning Engineer to join our forward-thinking team building the next generation of Intelligent Transportation Systems . In this role, you will design ...

Machine Learning Engineer

Addison, TX ยท On-site +1

$110K - $130K/yr

... machine learning models and algorithms that will improve Confie's business outcome/customer experience Perform data cleansing, analysis, and feature engineering using Python Ability to work with ...

As a Machine Learning Engineer II at 7-Eleven, you will collaborate with cross-functional teams and work closely with senior architects to implement scalable and efficient data solutions. Your ...

As a Machine Learning Engineer II at 7-Eleven, you will collaborate with cross-functional teams and work closely with senior architects to implement scalable and efficient data solutions. Your ...

As a Machine Learning Engineer II at 7-Eleven, you will collaborate with cross-functional teams and work closely with senior architects to implement scalable and efficient data solutions. Your ...

As a Machine Learning Engineer, you will play a crucial role in developing and deploying cutting-edge machine learning models and solutions to enhance various aspects of our business operations, from ...

Lead Machine Learning Engineer

Plano, TX ยท 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 ...

Lead Machine Learning Engineer

Plano, TX ยท On-site

$98K - $129K/yr

Lead Machine Learning Engineer Join the Dealer Tech division within Capital One's Financial Services Technology group, where we develop and support cutting edge technological solutions that ...

Lead Machine Learning Engineer

Plano, TX ยท On-site

$98K - $129K/yr

Lead Machine Learning Engineer Join the Dealer Tech division within Capital One's Financial Services Technology group, where we develop and support cutting edge technological solutions that ...

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 ...

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 ...

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 ...

Lead Machine Learning Engineer

Plano, TX

$98K - $129K/yr

Lead Machine Learning Engineer As a Capital One Lead Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing Generative AI and advanced agentic systems at scale.

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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 Sep 2, 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 biotech?

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?

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 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:

Infographic showing various Machine Learning Engineer Biotech job openings in Dallas, TX as of August 2026, with employment types broken down into 90% Full Time, and 10% Contract. Highlights an 85% In-person, and 15% Remote job distribution, with an average salary of $127,383 per year, or $61.2 per hour.

Machine Learning Engineer

TeleWorld Solutions Inc

Plano, TX โ€ข On-site

Full-time

Posted 21 days ago


Job description

Overview

TeleWorld Solutions is seeking a Machine Learning Engineer for our team! As a Performance Assurance Machine Learning Engineer, you will work under the coaching of Senior and Lead engineers of the Data Science & Tools Team to analyze Samsung's deployed network elements. You will utilize skills to query databases to extract data, use skills in Python or R to analyze data such that you can identify 4G/5G network infrastructure and performance issues and build prediction models, ad-hoc tools, and dashboards to communicate your findings with your team and peers.

TeleWorld Solutions is a strategic wireless engineering and consulting firm offering network operators, OEMs and tower companies turnkey design, optimization, network dimensioning and deployment services.ย 

With the experience of hundreds of thousands of successful implementations, including macro, DAS, Small Cells, and Wi-Fi, the world's leading network operators and OEMs trust our knowledge and experience to plan, perform, troubleshoot, and implement an array of technologies and solutions.

Come join our Veteran-Friendly Team. The Company with Great Benefits and certified as "A Great Place to Work".

Responsibilities
  • 7+ years of professional experience in Data Science, Data Analytics, and/or Data Engineering with abilities to work with large datasets using demonstrated statistical, predictive modeling and machine learning methods.
  • 3-5 years demonstrated experience on designing, deploying, and maintaining large scale ML systems in a production environment.
  • Work closely with the internal and external stakeholders to explore relationships of 4G/5G KPI measurements and targets (KPI, KQI) for 4G/5G RAN product acceptance and performance monitoring.
  • Collaborate with RF engineers, network engineers, data scientists, platform engineers, product teams, and operations stakeholders to ensure ML outputs are technically accurate, interpretable, and operationally useful.
  • Utilize A/B testing, statistical, and machine learning models to build robust mechanism for product & feature performance analysis, for evaluation of new product & SW releases and 3rd party product evaluation.
  • Aid in product & feature performance analysis, evaluation of new product & SW releases and 3rd party product evaluation using analytics/data science to drive intelligent business decisions.
  • Work with the team to proactively define and interpret data/metrics/KPIs, analyze results, and provide insights to determine operational impact, trends and opportunities for all the 4G/5G RAN products.
  • Prototyping use cases, implementing automations, and developing tools to support and augment manual or repetitive efforts.
  • Communicate key findings to stakeholders using visualizations and/or other suitable methods.
  • Excellent verbal and written communication skills to communicate technical and complex concepts in an easy-to-follow progression.
  • Able to compile analysis output and findings into a succinct story for technical and non-technical audiences.
  • Adapt to changes in a dynamic business environment and, support management initiatives.
Qualifications
  • Graduate Degree in Computer Science, Statistics, Data Science or a related Data Engineering with 7+ years of professional experience is preferred.
  • Programming experience: Python & Spark (preferred) and/or other languages such as R , SQL, Hive, Spark, Javascript, Visual Basic, C++, shell scripting in a linux or IDE environment such as VSCODE, Jupyter, RStudio, etc.
  • Cloud Development Experience - AWS/Azure/Google utilizing cloud providers such as Databricks or Snowflake
  • Machine learning expertise: GLM Regression (Linear, Logistic, Multinomial), Decision Tree (including Boosted Trees, Random Forest), kMeans/Hierarchical Clustering, Principle Component Analysis, t-SNE, Neural Networks such as transformers and auto-encoders, Bayesian Regression, and Times Series Modeling.
  • Experience using data with high-volume (1TB+) & high-dimensionality (500+ variables per schema), especially within a big data framework (HaDoop, Citus, MongoDB, etc).
  • Experience performing Data Wrangling, Exploratory Data Analysis (EDA), Correlation Analysis, Statistical Methodologies (distributions, hypothesis testing, confidence intervals) & Significance Testing, A/B Testing.
  • Experience with MLOPS concepts and environments such as MLFLOW a plus.
  • Experience with basic linux administration and software development in a linux environment.
  • Experience in hardware resource management and configuration - CUDA, Docker, KubeFlow, Kubernetes, etc a plus
  • Must possess qualities of being curious and eagerness to learn .
  • Experience with data visualization and ability to quickly grasp statistical methods, and methodologies. Maintain a strong command of current data analytics technology trends, including emerging paradigms and practices.
  • Demonstrated research and problem solving skills via prior work experience. Experience with wireless infrastructure provider and/or operator is desired.
  • Technical knowledge of any wireless technology & procedures including CDMA/EVDO/LTE/Volte and/or 5G a plus.
  • Experience with evaluating service performance trends and proactively defining RAN system performance related issues a plus.
  • Experience of software version control, coding best practices, and use of development management software such as github, bitbucket, etc is desired.
  • Must have a strong work ethic, integrity and work extremely well independently or in a team environment.

Physical/Mental Demands and Working Conditions: The position requires the ability to perform the essential duties and responsibilities in the following environment:

  • Excellent interpersonal and communication skills. Must be skilled in developing and maintaining good working relationships with all appropriate levels within and outside the company.
  • Operate a computer keyboard and view a video display terminal more than 75% of work time in an office work environment

Join Our Veteran-Friendly Team:

Are you a veteran or a veteran spouse with expertise in telecommunications? Join our team at TeleWorld Solutions, where we value your military experience and provide great benefits. We invite all veterans and veteran spouses to bring their skills and dedication to our team.

TeleWorld Solutions is committed to employing a diverse workforce and provides Equal Employment Opportunity for all individuals regardless of race, color, religion, gender, age, national origin, marital status, sexual orientation, gender identity, status as a protected veteran, genetic information, status as a qualified individual with a disability, or any other characteristic protected by law.

Employment Type: FULL_TIME