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Remote Machine Learning Jobs in Manitoba (NOW HIRING)

Remote with Canada Lieu : A distance, au Canada About the Position The Geodata Scientist role at ... Evaluate emerging machine learning, artificial intelligence, and uncertainty quantification ...

Our solutions help the world's biggest brands leverage artificial intelligence, machine learning ... This position is remote and open to candidates within Canada. As Senior Software Developer, You ...

This is a permanent position that is completely remote! Our client is a fintech company based out of Vancouver You Have: * 3 - 5+ Years experience working in Data Engineering/Data Science utilizing R ...

This is a permanent position that is completely remote! Our client is a fintech company based out of Vancouver You Have: * 3 - 5+ Years experience working in Data Engineering/Data Science utilizing R ...

Remote Machine Learning information

See Manitoba salary details

$25K

$142.8K

$228.5K

How much do remote machine learning jobs pay per year?

As of Jul 15, 2026, the average yearly pay for remote machine learning in Manitoba is $142,783.00, according to ZipRecruiter salary data. Most workers in this role earn between $120,000.00 and $171,500.00 per year, depending on experience, location, and employer.

What engineer makes $500,000 a year?

Senior machine learning engineers with extensive experience, advanced skills in deep learning and data modeling, and often working at large tech companies or in specialized industries can earn salaries approaching or exceeding $500,000 annually. Compensation may include base salary, bonuses, and stock options, especially in high-demand markets.

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

To thrive as a Remote Machine Learning Engineer, you need a strong background in mathematics, statistics, programming (often Python), and experience with machine learning frameworks, typically supported by a relevant degree. Familiarity with tools such as TensorFlow, PyTorch, cloud platforms (like AWS or GCP), and version control systems is crucial. Strong problem-solving abilities, self-management, and effective virtual communication distinguish top performers in remote settings. These competencies ensure the engineer can build effective models, collaborate across distributed teams, and deliver impactful solutions independently.

How to make 2000 a week working from home?

Remote machine learning professionals can earn $2,000 or more weekly by taking on high-paying freelance projects, consulting roles, or working for companies that offer remote positions with competitive salaries. Building specialized skills in programming, data analysis, and tools like Python, TensorFlow, or cloud platforms can increase earning potential. Consistent work, a strong portfolio, and networking are key to reaching this income level from home.

What Are Remote Machine Learning Jobs?

Machine learning is a method of analyzing data via automating analytical model building. The premise is that systems can learn from data. Machine learning positions include machine learning engineer, computer vision engineer, and senior deep learning engineer. In a remote machine learning job, you work from home in a branch of artificial intelligence performing duties related to computational processing and data. Your goal is to design models that solve business problems, such as helping organizations avoid unknown risks or find profitable opportunities. Your responsibilities include maintaining data pipelines, performing model research and implementation, building machine learning systems, and onboarding new utilities.

What is a remote machine learning job?

A remote machine learning job involves working with algorithms, data, and models to develop predictive systems or automate tasks, all while working from a location outside of a traditional office setting. Professionals in this role use techniques from statistics and computer science to analyze data, train machine learning models, and deploy solutions for real-world applications. Remote machine learning jobs can span various industries, including technology, healthcare, finance, and e-commerce. These roles typically require strong programming skills, knowledge of machine learning frameworks, and the ability to communicate findings effectively with team members or stakeholders. Working remotely offers flexibility, but also requires discipline and self-motivation to succeed.

What are some effective strategies for collaborating with team members while working remotely as a Machine Learning Engineer?

Collaboration in a remote Machine Learning role often relies on clear communication through digital tools such as Slack, Zoom, and project management platforms like Jira or Asana. Regular check-ins and stand-up meetings help keep everyone aligned on project goals and timelines. Sharing code and models via version control systems (like Git) and using collaborative notebooks (such as JupyterHub or Google Colab) are also common practices. Building strong documentation habits and proactively seeking feedback can help ensure smooth teamwork and project success, even across different time zones.

What is the difference between Remote Machine Learning vs Data Scientist?

AspectRemote Machine LearningData Scientist
Required CredentialsBachelor's/Master's in CS, ML certificationsBachelor's/Master's in CS, Statistics, or related field
Work EnvironmentRemote, collaborative teams, tech companiesRemote or on-site, diverse industries, analytics focus
Industry UsageTech, AI startups, researchFinance, healthcare, e-commerce, tech
Search & Comparison IntentOften compared for technical roles in AI/MLBroader data analysis roles, but overlapping skills

Remote Machine Learning specialists focus on developing algorithms and models primarily in tech environments, often requiring advanced programming and ML knowledge. Data Scientists analyze data to extract insights, sometimes utilizing ML techniques. While both roles share skills and credentials, Remote Machine Learning emphasizes model development, whereas Data Scientists focus on data analysis and interpretation.

Are there remote machine learning jobs?

Yes, remote machine learning jobs are widely available across various industries, often requiring skills in programming, data analysis, and familiarity with tools like Python, TensorFlow, or PyTorch. Many companies offer flexible schedules and remote work options for qualified candidates, especially in tech and research sectors.

Will MLE be replaced by AI?

Machine Learning Engineers (MLEs) design, develop, and deploy AI models, and their role involves understanding algorithms, data preprocessing, and model optimization. While AI automation tools can handle certain tasks, MLEs are essential for creating, fine-tuning, and maintaining complex AI systems, making complete replacement unlikely in the near term.
What are popular job titles related to Remote Machine Learning jobs in Manitoba? For Remote Machine Learning jobs in Manitoba, the most frequently searched job titles are:
What job categories do people searching Remote Machine Learning jobs in Manitoba look for? The top searched job categories for Remote Machine Learning jobs in Manitoba are:

Geodata Scientist

ALS

Winnipeg, MB โ€ข Remote

Other

Medical, Dental, Vision, Life, Retirement, PTO

Posted 6 days ago


Job description

At ALS, we encourage you to dream big.

When you join us, you'll be part of a global team harnessing the power of scientific testing and data-driven insights to build a healthier future.

French and English versions below / Versions francaise et anglaise ci-dessous

Location: Remote with Canada

Lieu : A distance, au Canada

About the Position

The Geodata Scientist role at ALS Geoanalytics suits someone who enjoys solving complex geoscience problems and applying machine learning to real-world mineral exploration challenges. You will deliver consulting projects focused on prospectivity analysis, geoscience data integration, and predictive modelling, collaborating with clients and internal teams to produce actionable exploration insights, while also contributing to the advancement of ALS Geoanalytics' platforms by evaluating and implementing new ML methodologies and workflow improvements.

Specific Responsibilities:

Innovation and Software platform support

  • Execute mineral exploration and geoscience consulting projects using machine learning, statistical analysis, and spatial data integration techniques to support exploration in 2D and 3D.

  • Effective collaboration with multidisciplinary teams of geologists, geophysicists, geochemists, and data scientists.

  • Process, analyze, and interpret geophysical, geological, geochemical, remote sensing, and drilling datasets.

  • Develop mineral prospectivity models, geological classification models, and geoscience data products using SmartSuite and supporting analytical tools and workflows.

  • Prepare high quality technical reports, presentations, maps, and client deliverables.

  • Present project results and recommendations to clients and stakeholders.

  • Support project proposal development, project planning, and technical scoping activities.

  • Adapt analytical workflows to address the unique challenges and data constraints associated with each project.

  • Ensure up to date completion of timelogs/timesheets and business development activities using management system software (e.g., Zoho and HubSpot).

Innovation and Software platform support

  • Contribute to the ongoing development and enhancement of 2D and 3D machine learning mineral prospectivity and related workflows and capabilities.

  • Evaluate emerging machine learning, artificial intelligence, and uncertainty quantification methodologies for potential incorporation into company products and services.

  • Assist in developing, testing, and validating new analytical tools and model diagnostics.

  • Support software quality assurance, workflow optimization, and technical documentation.

  • Collaborate with product and development teams to translate consulting experience into platform improvements and new product capabilities.

  • Contribute to internal research and development initiatives focused on advancing geoscience analytics and exploration targeting methodologies.

Collaboration

  • Participate in internal technical sessions to stay current on ALS consulting services and related offerings.

  • Work with business development and marketing to collect and relay client feedback that supports improved collateral, brand awareness, and engagement.

  • Occasional travel to office for training, collaboration, client meetings, and team building events.

  • Provide structured updates to leadership on project task status and outlook.

Health and Safety

  • Observe established safety regulations and comply with all ALS health and safety policies and procedures.

Required Knowledge, Skills & Abilities:

  • Familiarity with geological sciences, mineral deposits, and mining/exploration.

  • Experience applying machine learning to mineral exploration, geological modelling, mineral prospectivity mapping, or related geoscience applications.

  • Experience with uncertainty quantification, probabilistic modelling, Bayesian methods, or explainable AI techniques.

  • Familiarity with geophysical, geological, geochemical, remote sensing, and drillhole datasets.

  • Experience with cloud computing, scalable data processing, or software development practices.

  • Experience presenting technical results to clients, industry groups, or scientific audiences.

  • Strong organizational skills and attention to detail as it relates to creating and following templates, version control, documentation, and established procedures.

  • Excellent verbal and written communication skills (English required; English-French preferred).

  • Ability to communicate complex technical concepts to both technical and non-technical audiences.

  • Ability to work independently while collaborating effectively within multidisciplinary teams.

  • Practiced in working with geospatial datasets and spatial analysis workflows.

  • Strong understanding of machine learning and statistical modelling techniques.

  • Proficiency in Python and common scientific computing libraries.

  • Strong writing skills, with the ability to draft clear, structured content and summarize technical inputs for proposals, marketing materials, and client communications.

Required Qualifications:

  • M.Sc. or Ph.D. in Geophysics, Geology, Geological Engineering, Mineral Engineering, Data Science, Computer Science, or a related discipline.

  • Professional registration in relevant jurisdiction. (P.Geo, P.Eng) or the ability to obtain such designation.

Physical Demands:

  • Manual dexterity to perform intricate and/or repetitive tasks;

  • Wear issued personal protective equipment (PPE) such as dust masks, gloves etc., when required;

  • Ability to sit at a desk and do general office work, which includes periodic sedentary responsibilities;

  • Ability to conduct physically demanding geological field work in remote areas.

Our benefits include

  • An estimated annual salary between $90,000 - $100,000 CAD at the time of posting. Individual compensation is determined by factors such as job-related skills, relevant experience, education and/or training.

  • Comprehensive benefit package specific to your work status (including extended medical, dental, and vision coverage, access to company perks, life and disability insurance, retirement plan with company match, employee assistance and wellness programs)

  • Additional vacation days for years of service

  • Business support for education or training after 9 months with the company

  • Learning & development opportunities (unlimited access to e-learnings and more)

Please note: Benefits vary based on employee status.

A propos du poste

Le role de Geoscientifique des donnees chez ALS Geoanalytics convient a une personne qui aime resoudre des problemes geoscientifiques complexes et appliquer l'apprentissage automatique aux defis concrets de l'exploration minerale. Vous realiserez des projets de conseil axes sur l'analyse de prospectivite, l'integration de donnees geoscientifiques et la modelisation predictive, en collaborant avec les clients et les equipes internes pour produire des informations exploitables, tout en contribuant a l'avancement des plateformes d'ALS Geoanalytics en evaluant et en mettant en uvre de nouvelles methodologies d'apprentissage automatique et des ameliorations de flux de travail.

Responsabilites specifiques :

Conseil en exploration

  • Executer des projets de conseil en exploration minerale et en geosciences en utilisant l'apprentissage automatique, l'analyse statistique et des techniques d'integration de donnees spatiales en 2D et 3D.

  • Collaborer efficacement avec des equipes multidisciplinaires de geologues, geophysiciens, geochimistes et scientifiques des donnees.

  • Traiter, analyser et interpreter des jeux de donnees geophysiques, geologiques, geochimiques, de teledetection et de forage.

  • Developper des modeles de prospectivite minerale, des modeles de classification geologique et des produits de donnees geoscientifiques a l'aide de SmartSuite et des outils analytiques associes.

  • Preparer des rapports techniques de haute qualite, des presentations, des cartes et des livrables clients.

  • Presenter les resultats des projets et les recommandations aux clients et aux parties prenantes.

  • Soutenir le developpement des propositions de projets, la planification et les activites de cadrage technique.

  • Adapter les flux de travail analytiques aux defis uniques et aux contraintes de donnees propres a chaque projet.

  • Assurer la mise a jour des feuilles de temps et des activites de developpement des affaires a l'aide des logiciels de gestion (ex. : Zoho et HubSpot).

Innovation et soutien a la plateforme logicielle

  • Contribuer au developpement et a l'amelioration continus des flux de travail et capacites de prospectivite minerale par apprentissage automatique en 2D et 3D.

  • Evaluer les methodologies emergentes en apprentissage automatique, intelligence artificielle et quantification de l'incertitude en vue de leur integration dans les produits et services de l'entreprise.

  • Participer au developpement, aux tests et a la validation de nouveaux outils analytiques et diagnostics de modeles.

  • Soutenir l'assurance qualite des logiciels, l'optimisation des flux de travail et la documentation technique.

  • Collaborer avec les equipes produit et developpement pour traduire l'experience conseil en ameliorations de la plateforme et en nouvelles fonctionnalites.

  • Contribuer aux initiatives internes de recherche et developpement visant a faire progresser les analyses geoscientifiques et les methodologies de ciblage exploratoire.

Collaboration

  • Participer aux sessions techniques internes pour demeurer a jour sur les services de conseil d'ALS et les offres connexes.

  • Travailler avec les equipes de developpement des affaires et de marketing pour recueillir et transmettre les commentaires des clients afin d'ameliorer les supports de communication et la notoriete de la marque.

  • Voyager occasionnellement au bureau pour des formations, des reunions clients et des evenements d'equipe.

  • Fournir des mises a jour structurees a la direction sur l'etat d'avancement des taches et les perspectives de projets.

Sante et securite

  • Respecter les reglements de securite etablis et se conformer a toutes les politiques et procedures de sante et securite d'ALS.

Connaissances, competences et aptitudes requises :

  • Connaissance des sciences geologiques, des gisements mineraux et de l'exploration/exploitation miniere.

  • Experience de l'application de l'apprentissage automatique a l'exploration minerale, a la modelisation geologique, a la cartographie de prospectivite ou a des applications geoscientifiques connexes.

  • Experience en quantification de l'incertitude, modelisation probabiliste, methodes bayesiennes ou techniques d'IA explicable.

  • Familiarite avec les jeux de donnees geophysiques, geologiques, geochimiques, de teledetection et de forage.

  • Experience en informatique en nuage, traitement de donnees a grande echelle ou pratiques de developpement logiciel.

  • Experience de presentation de resultats techniques a des clients, groupes industriels ou publics scientifiques.

  • Solides competences organisationnelles et souci du detail en ce qui concerne la creation et le respect de modeles, le controle des versions, la documentation et les procedures etablies.

  • Excellentes aptitudes a la communication verbale et ecrite (anglais obligatoire ; bilinguisme anglais-francais souhaite).

  • Capacite a communiquer des concepts techniques complexes a des publics techniques et non techniques.

  • Capacite a travailler de maniere autonome tout en collaborant efficacement au sein d'equipes multidisciplinaires.

  • Experience dans le travail avec des jeux de donnees geospatiales et des flux d'analyse spatiale.

  • Solide comprehension des techniques d'apprentissage automatique et de modelisation statistique.

  • Maitrise de Python et des bibliotheques courantes de calcul scientifique.

  • Excellentes competences redactionnelles, avec la capacite de rediger du contenu clair et structure pour des propositions, des supports marketing et des communications clients.

Qualifications requises :

  • M.Sc. ou Ph.D. en geophysique, geologie, genie geologique, genie minier, science des donnees, informatique ou discipline connexe.

  • Inscription professionnelle dans la juridiction concernee (P.Geo., Ing.) ou capacite a obtenir cette designation.

Exigences physiques :

  • Dexterite manuelle pour effectuer des taches complexes et/ou repetitives.

  • Port des equipements de protection individuelle (EPI) requis (masques anti-poussiere, gants, etc.).

  • Capacite a travailler a un bureau et a effectuer des taches de bureau generales, incluant des responsabilites sedentaires periodiques.

  • Capacite a effectuer des travaux de terrain geologiques exigeants physiquement dans des zones eloignees.

Nos avantages incluent :

  • Un salaire annuel estime entre$90,000et $100,000 CADau moment de la publication. La remuneration individuelle est determinee par des facteurs tels que les competences liees au poste, l'experience pertinente, la formation et/ou l'education.

  • Un regime d'avantages sociaux complet adapte a votre statut d'emploi (incluant la couverture medicale etendue, dentaire et visuelle, l'acces aux avantages de l'entreprise, l'assurance vie et invalidite, un regime de retraite avec participation de l'employeur, des...